6c84c8bf9b
Add generic support for the OpenACC 2.6 `acc_get_property' and `acc_get_property_string' routines, as well as full handlers for the host and the NVPTX offload targets and minimal handlers for the HSA, Intel MIC, and AMD GCN offload targets. Included are C/C++ and Fortran tests that, in particular, print the property values for acc_property_vendor, acc_property_memory, acc_property_free_memory, acc_property_name, and acc_property_driver. The output looks as follows: Vendor: GNU Name: GOMP Total memory: 0 Free memory: 0 Driver: 1.0 with the host driver (where the memory related properties are not supported for the host device and yield 0, conforming to the standard) and output like: Vendor: Nvidia Total memory: 12651462656 Free memory: 12202737664 Name: TITAN V Driver: CUDA Driver 9.1 with the NVPTX driver. 2019-12-22 Maciej W. Rozycki <macro@codesourcery.com> Frederik Harwath <frederik@codesourcery.com> Thomas Schwinge <tschwinge@codesourcery.com> include/ * gomp-constants.h (gomp_device_property): New enum. libgomp/ * libgomp.h (gomp_device_descr): Add `get_property_func' member. * libgomp-plugin.h (gomp_device_property_value): New union. (gomp_device_property_value): New prototype. * openacc.h (acc_device_t): Add `acc_device_current' enumeration constant. (acc_device_property_t): New enum. (acc_get_property, acc_get_property_string): New prototypes. * oacc-init.c (acc_get_device_type): Also assert that result is not `acc_device_current'. (get_property_any, acc_get_property, acc_get_property_string): New functions. * openacc.f90 (openacc_kinds): Add `acc_device_current' and `acc_property_memory', `acc_property_free_memory', `acc_property_name', `acc_property_vendor' and `acc_property_driver' constants. Add `acc_device_property' data type. (openacc_internal): Add `acc_get_property' and `acc_get_property_string' interfaces. Add `acc_get_property_h', `acc_get_property_string_h', `acc_get_property_l' and `acc_get_property_string_l'. * oacc-host.c (host_get_property): New function. (host_dispatch): Wire it. * target.c (gomp_load_plugin_for_device): Handle `get_property'. * libgomp.map (OACC_2.6): Add `acc_get_property', `acc_get_property_h_', `acc_get_property_string' and `acc_get_property_string_h_' symbols. * libgomp.texi (OpenACC Runtime Library Routines): Add `acc_get_property'. (acc_get_property): New node. * plugin/plugin-gcn.c (GOMP_OFFLOAD_get_property): New function (stub). * plugin/plugin-hsa.c (GOMP_OFFLOAD_get_property): New function. * plugin/plugin-nvptx.c (CUDA_CALLS): Add `cuDeviceGetName', `cuDeviceTotalMem', `cuDriverGetVersion' and `cuMemGetInfo' calls. (GOMP_OFFLOAD_get_property): New function. (struct ptx_device): Add new field "name". (cuda_driver_version_s): Add new static variable ... (nvptx_init): ... and init from here. * testsuite/libgomp.oacc-c-c++-common/acc_get_property.c: New test. * testsuite/libgomp.oacc-c-c++-common/acc_get_property-2.c: New test. * testsuite/libgomp.oacc-c-c++-common/acc_get_property-3.c: New test. * testsuite/libgomp.oacc-c-c++-common/acc_get_property-aux.c: New file with test helper functions. * testsuite/libgomp.oacc-fortran/acc_get_property.f90: New test. liboffloadmic/ * plugin/libgomp-plugin-intelmic.cpp (GOMP_OFFLOAD_get_property): New function. Reviewed-by: Thomas Schwinge <thomas@codesourcery.com> Co-Authored-By: Frederik Harwath <frederik@codesourcery.com> Co-Authored-By: Thomas Schwinge <tschwinge@codesourcery.com> From-SVN: r279710
1938 lines
52 KiB
C
1938 lines
52 KiB
C
/* Plugin for NVPTX execution.
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Copyright (C) 2013-2019 Free Software Foundation, Inc.
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Contributed by Mentor Embedded.
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This file is part of the GNU Offloading and Multi Processing Library
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(libgomp).
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Libgomp is free software; you can redistribute it and/or modify it
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under the terms of the GNU General Public License as published by
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the Free Software Foundation; either version 3, or (at your option)
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any later version.
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Libgomp is distributed in the hope that it will be useful, but WITHOUT ANY
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WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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FOR A PARTICULAR PURPOSE. See the GNU General Public License for
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more details.
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Under Section 7 of GPL version 3, you are granted additional
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permissions described in the GCC Runtime Library Exception, version
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3.1, as published by the Free Software Foundation.
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You should have received a copy of the GNU General Public License and
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a copy of the GCC Runtime Library Exception along with this program;
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see the files COPYING3 and COPYING.RUNTIME respectively. If not, see
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<http://www.gnu.org/licenses/>. */
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/* Nvidia PTX-specific parts of OpenACC support. The cuda driver
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library appears to hold some implicit state, but the documentation
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is not clear as to what that state might be. Or how one might
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propagate it from one thread to another. */
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#define _GNU_SOURCE
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#include "openacc.h"
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#include "config.h"
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#include "libgomp-plugin.h"
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#include "oacc-plugin.h"
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#include "gomp-constants.h"
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#include "oacc-int.h"
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#include <pthread.h>
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#include <cuda.h>
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#include <stdbool.h>
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#include <limits.h>
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#include <string.h>
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#include <stdio.h>
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#include <unistd.h>
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#include <assert.h>
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#include <errno.h>
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#if CUDA_VERSION < 6000
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extern CUresult cuGetErrorString (CUresult, const char **);
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#define CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_MULTIPROCESSOR 82
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#endif
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#if CUDA_VERSION >= 6050
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#undef cuLinkCreate
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#undef cuLinkAddData
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CUresult cuLinkAddData (CUlinkState, CUjitInputType, void *, size_t,
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const char *, unsigned, CUjit_option *, void **);
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CUresult cuLinkCreate (unsigned, CUjit_option *, void **, CUlinkState *);
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#else
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typedef size_t (*CUoccupancyB2DSize)(int);
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CUresult cuLinkAddData_v2 (CUlinkState, CUjitInputType, void *, size_t,
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const char *, unsigned, CUjit_option *, void **);
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CUresult cuLinkCreate_v2 (unsigned, CUjit_option *, void **, CUlinkState *);
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CUresult cuOccupancyMaxPotentialBlockSize(int *, int *, CUfunction,
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CUoccupancyB2DSize, size_t, int);
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#endif
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#define DO_PRAGMA(x) _Pragma (#x)
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#if PLUGIN_NVPTX_DYNAMIC
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# include <dlfcn.h>
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struct cuda_lib_s {
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# define CUDA_ONE_CALL(call) \
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__typeof (call) *call;
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# define CUDA_ONE_CALL_MAYBE_NULL(call) \
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CUDA_ONE_CALL (call)
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#include "cuda-lib.def"
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# undef CUDA_ONE_CALL
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# undef CUDA_ONE_CALL_MAYBE_NULL
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} cuda_lib;
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/* -1 if init_cuda_lib has not been called yet, false
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if it has been and failed, true if it has been and succeeded. */
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static signed char cuda_lib_inited = -1;
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/* Dynamically load the CUDA runtime library and initialize function
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pointers, return false if unsuccessful, true if successful. */
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static bool
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init_cuda_lib (void)
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{
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if (cuda_lib_inited != -1)
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return cuda_lib_inited;
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const char *cuda_runtime_lib = "libcuda.so.1";
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void *h = dlopen (cuda_runtime_lib, RTLD_LAZY);
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cuda_lib_inited = false;
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if (h == NULL)
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return false;
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# define CUDA_ONE_CALL(call) CUDA_ONE_CALL_1 (call, false)
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# define CUDA_ONE_CALL_MAYBE_NULL(call) CUDA_ONE_CALL_1 (call, true)
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# define CUDA_ONE_CALL_1(call, allow_null) \
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cuda_lib.call = dlsym (h, #call); \
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if (!allow_null && cuda_lib.call == NULL) \
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return false;
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#include "cuda-lib.def"
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# undef CUDA_ONE_CALL
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# undef CUDA_ONE_CALL_1
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# undef CUDA_ONE_CALL_MAYBE_NULL
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cuda_lib_inited = true;
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return true;
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}
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# define CUDA_CALL_PREFIX cuda_lib.
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#else
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# define CUDA_ONE_CALL(call)
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# define CUDA_ONE_CALL_MAYBE_NULL(call) DO_PRAGMA (weak call)
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#include "cuda-lib.def"
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#undef CUDA_ONE_CALL_MAYBE_NULL
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#undef CUDA_ONE_CALL
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# define CUDA_CALL_PREFIX
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# define init_cuda_lib() true
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#endif
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#include "secure_getenv.h"
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#undef MIN
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#undef MAX
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#define MIN(X,Y) ((X) < (Y) ? (X) : (Y))
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#define MAX(X,Y) ((X) > (Y) ? (X) : (Y))
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/* Convenience macros for the frequently used CUDA library call and
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error handling sequence as well as CUDA library calls that
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do the error checking themselves or don't do it at all. */
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#define CUDA_CALL_ERET(ERET, FN, ...) \
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do { \
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unsigned __r \
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= CUDA_CALL_PREFIX FN (__VA_ARGS__); \
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if (__r != CUDA_SUCCESS) \
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{ \
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GOMP_PLUGIN_error (#FN " error: %s", \
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cuda_error (__r)); \
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return ERET; \
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} \
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} while (0)
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#define CUDA_CALL(FN, ...) \
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CUDA_CALL_ERET (false, FN, __VA_ARGS__)
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#define CUDA_CALL_ASSERT(FN, ...) \
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do { \
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unsigned __r \
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= CUDA_CALL_PREFIX FN (__VA_ARGS__); \
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if (__r != CUDA_SUCCESS) \
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{ \
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GOMP_PLUGIN_fatal (#FN " error: %s", \
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cuda_error (__r)); \
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} \
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} while (0)
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#define CUDA_CALL_NOCHECK(FN, ...) \
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CUDA_CALL_PREFIX FN (__VA_ARGS__)
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#define CUDA_CALL_EXISTS(FN) \
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CUDA_CALL_PREFIX FN
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static const char *
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cuda_error (CUresult r)
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{
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const char *fallback = "unknown cuda error";
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const char *desc;
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if (!CUDA_CALL_EXISTS (cuGetErrorString))
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return fallback;
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r = CUDA_CALL_NOCHECK (cuGetErrorString, r, &desc);
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if (r == CUDA_SUCCESS)
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return desc;
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return fallback;
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}
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/* Version of the CUDA Toolkit in the same MAJOR.MINOR format that is used by
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Nvidia, such as in the 'deviceQuery' program (Nvidia's CUDA samples). */
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static char cuda_driver_version_s[30];
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static unsigned int instantiated_devices = 0;
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static pthread_mutex_t ptx_dev_lock = PTHREAD_MUTEX_INITIALIZER;
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/* NVPTX/CUDA specific definition of asynchronous queues. */
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struct goacc_asyncqueue
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{
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CUstream cuda_stream;
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};
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struct nvptx_callback
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{
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void (*fn) (void *);
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void *ptr;
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struct goacc_asyncqueue *aq;
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struct nvptx_callback *next;
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};
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/* Thread-specific data for PTX. */
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struct nvptx_thread
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{
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/* We currently have this embedded inside the plugin because libgomp manages
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devices through integer target_ids. This might be better if using an
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opaque target-specific pointer directly from gomp_device_descr. */
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struct ptx_device *ptx_dev;
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};
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/* Target data function launch information. */
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struct targ_fn_launch
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{
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const char *fn;
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unsigned short dim[GOMP_DIM_MAX];
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};
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/* Target PTX object information. */
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struct targ_ptx_obj
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{
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const char *code;
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size_t size;
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};
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/* Target data image information. */
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typedef struct nvptx_tdata
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{
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const struct targ_ptx_obj *ptx_objs;
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unsigned ptx_num;
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const char *const *var_names;
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unsigned var_num;
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const struct targ_fn_launch *fn_descs;
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unsigned fn_num;
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} nvptx_tdata_t;
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/* Descriptor of a loaded function. */
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struct targ_fn_descriptor
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{
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CUfunction fn;
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const struct targ_fn_launch *launch;
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int regs_per_thread;
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int max_threads_per_block;
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};
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/* A loaded PTX image. */
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struct ptx_image_data
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{
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const void *target_data;
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CUmodule module;
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struct targ_fn_descriptor *fns; /* Array of functions. */
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struct ptx_image_data *next;
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};
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struct ptx_free_block
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{
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void *ptr;
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struct ptx_free_block *next;
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};
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struct ptx_device
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{
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CUcontext ctx;
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bool ctx_shared;
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CUdevice dev;
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int ord;
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bool overlap;
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bool map;
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bool concur;
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bool mkern;
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int mode;
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int clock_khz;
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int num_sms;
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int regs_per_block;
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int regs_per_sm;
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int warp_size;
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int max_threads_per_block;
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int max_threads_per_multiprocessor;
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int default_dims[GOMP_DIM_MAX];
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/* Length as used by the CUDA Runtime API ('struct cudaDeviceProp'). */
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char name[256];
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struct ptx_image_data *images; /* Images loaded on device. */
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pthread_mutex_t image_lock; /* Lock for above list. */
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struct ptx_free_block *free_blocks;
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pthread_mutex_t free_blocks_lock;
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struct ptx_device *next;
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};
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static struct ptx_device **ptx_devices;
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static inline struct nvptx_thread *
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nvptx_thread (void)
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{
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return (struct nvptx_thread *) GOMP_PLUGIN_acc_thread ();
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}
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/* Initialize the device. Return TRUE on success, else FALSE. PTX_DEV_LOCK
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should be locked on entry and remains locked on exit. */
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static bool
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nvptx_init (void)
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{
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int ndevs;
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if (instantiated_devices != 0)
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return true;
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if (!init_cuda_lib ())
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return false;
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CUDA_CALL (cuInit, 0);
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int cuda_driver_version;
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CUDA_CALL_ERET (NULL, cuDriverGetVersion, &cuda_driver_version);
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snprintf (cuda_driver_version_s, sizeof cuda_driver_version_s,
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"CUDA Driver %u.%u",
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cuda_driver_version / 1000, cuda_driver_version % 1000 / 10);
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CUDA_CALL (cuDeviceGetCount, &ndevs);
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ptx_devices = GOMP_PLUGIN_malloc_cleared (sizeof (struct ptx_device *)
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* ndevs);
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return true;
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}
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/* Select the N'th PTX device for the current host thread. The device must
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have been previously opened before calling this function. */
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static bool
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nvptx_attach_host_thread_to_device (int n)
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{
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CUdevice dev;
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CUresult r;
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struct ptx_device *ptx_dev;
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CUcontext thd_ctx;
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r = CUDA_CALL_NOCHECK (cuCtxGetDevice, &dev);
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if (r == CUDA_ERROR_NOT_PERMITTED)
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{
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/* Assume we're in a CUDA callback, just return true. */
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return true;
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}
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if (r != CUDA_SUCCESS && r != CUDA_ERROR_INVALID_CONTEXT)
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{
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GOMP_PLUGIN_error ("cuCtxGetDevice error: %s", cuda_error (r));
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return false;
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}
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if (r != CUDA_ERROR_INVALID_CONTEXT && dev == n)
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return true;
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else
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{
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CUcontext old_ctx;
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ptx_dev = ptx_devices[n];
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if (!ptx_dev)
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{
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GOMP_PLUGIN_error ("device %d not found", n);
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return false;
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}
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CUDA_CALL (cuCtxGetCurrent, &thd_ctx);
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/* We don't necessarily have a current context (e.g. if it has been
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destroyed. Pop it if we do though. */
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if (thd_ctx != NULL)
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CUDA_CALL (cuCtxPopCurrent, &old_ctx);
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CUDA_CALL (cuCtxPushCurrent, ptx_dev->ctx);
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}
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return true;
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}
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static struct ptx_device *
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nvptx_open_device (int n)
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{
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struct ptx_device *ptx_dev;
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CUdevice dev, ctx_dev;
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CUresult r;
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int async_engines, pi;
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CUDA_CALL_ERET (NULL, cuDeviceGet, &dev, n);
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ptx_dev = GOMP_PLUGIN_malloc (sizeof (struct ptx_device));
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ptx_dev->ord = n;
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ptx_dev->dev = dev;
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ptx_dev->ctx_shared = false;
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r = CUDA_CALL_NOCHECK (cuCtxGetDevice, &ctx_dev);
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if (r != CUDA_SUCCESS && r != CUDA_ERROR_INVALID_CONTEXT)
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{
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GOMP_PLUGIN_error ("cuCtxGetDevice error: %s", cuda_error (r));
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return NULL;
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}
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if (r != CUDA_ERROR_INVALID_CONTEXT && ctx_dev != dev)
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{
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/* The current host thread has an active context for a different device.
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Detach it. */
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CUcontext old_ctx;
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CUDA_CALL_ERET (NULL, cuCtxPopCurrent, &old_ctx);
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}
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CUDA_CALL_ERET (NULL, cuCtxGetCurrent, &ptx_dev->ctx);
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if (!ptx_dev->ctx)
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CUDA_CALL_ERET (NULL, cuCtxCreate, &ptx_dev->ctx, CU_CTX_SCHED_AUTO, dev);
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else
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ptx_dev->ctx_shared = true;
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CUDA_CALL_ERET (NULL, cuDeviceGetAttribute,
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&pi, CU_DEVICE_ATTRIBUTE_GPU_OVERLAP, dev);
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ptx_dev->overlap = pi;
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CUDA_CALL_ERET (NULL, cuDeviceGetAttribute,
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&pi, CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY, dev);
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ptx_dev->map = pi;
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CUDA_CALL_ERET (NULL, cuDeviceGetAttribute,
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&pi, CU_DEVICE_ATTRIBUTE_CONCURRENT_KERNELS, dev);
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ptx_dev->concur = pi;
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CUDA_CALL_ERET (NULL, cuDeviceGetAttribute,
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&pi, CU_DEVICE_ATTRIBUTE_COMPUTE_MODE, dev);
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ptx_dev->mode = pi;
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CUDA_CALL_ERET (NULL, cuDeviceGetAttribute,
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&pi, CU_DEVICE_ATTRIBUTE_INTEGRATED, dev);
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ptx_dev->mkern = pi;
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CUDA_CALL_ERET (NULL, cuDeviceGetAttribute,
|
|
&pi, CU_DEVICE_ATTRIBUTE_CLOCK_RATE, dev);
|
|
ptx_dev->clock_khz = pi;
|
|
|
|
CUDA_CALL_ERET (NULL, cuDeviceGetAttribute,
|
|
&pi, CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT, dev);
|
|
ptx_dev->num_sms = pi;
|
|
|
|
CUDA_CALL_ERET (NULL, cuDeviceGetAttribute,
|
|
&pi, CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_BLOCK, dev);
|
|
ptx_dev->regs_per_block = pi;
|
|
|
|
/* CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_MULTIPROCESSOR is defined only
|
|
in CUDA 6.0 and newer. */
|
|
r = CUDA_CALL_NOCHECK (cuDeviceGetAttribute, &pi,
|
|
CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_MULTIPROCESSOR,
|
|
dev);
|
|
/* Fallback: use limit of registers per block, which is usually equal. */
|
|
if (r == CUDA_ERROR_INVALID_VALUE)
|
|
pi = ptx_dev->regs_per_block;
|
|
else if (r != CUDA_SUCCESS)
|
|
{
|
|
GOMP_PLUGIN_error ("cuDeviceGetAttribute error: %s", cuda_error (r));
|
|
return NULL;
|
|
}
|
|
ptx_dev->regs_per_sm = pi;
|
|
|
|
CUDA_CALL_ERET (NULL, cuDeviceGetAttribute,
|
|
&pi, CU_DEVICE_ATTRIBUTE_WARP_SIZE, dev);
|
|
if (pi != 32)
|
|
{
|
|
GOMP_PLUGIN_error ("Only warp size 32 is supported");
|
|
return NULL;
|
|
}
|
|
ptx_dev->warp_size = pi;
|
|
|
|
CUDA_CALL_ERET (NULL, cuDeviceGetAttribute, &pi,
|
|
CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK, dev);
|
|
ptx_dev->max_threads_per_block = pi;
|
|
|
|
CUDA_CALL_ERET (NULL, cuDeviceGetAttribute, &pi,
|
|
CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_MULTIPROCESSOR, dev);
|
|
ptx_dev->max_threads_per_multiprocessor = pi;
|
|
|
|
r = CUDA_CALL_NOCHECK (cuDeviceGetAttribute, &async_engines,
|
|
CU_DEVICE_ATTRIBUTE_ASYNC_ENGINE_COUNT, dev);
|
|
if (r != CUDA_SUCCESS)
|
|
async_engines = 1;
|
|
|
|
for (int i = 0; i != GOMP_DIM_MAX; i++)
|
|
ptx_dev->default_dims[i] = 0;
|
|
|
|
CUDA_CALL_ERET (NULL, cuDeviceGetName, ptx_dev->name, sizeof ptx_dev->name,
|
|
dev);
|
|
|
|
ptx_dev->images = NULL;
|
|
pthread_mutex_init (&ptx_dev->image_lock, NULL);
|
|
|
|
ptx_dev->free_blocks = NULL;
|
|
pthread_mutex_init (&ptx_dev->free_blocks_lock, NULL);
|
|
|
|
return ptx_dev;
|
|
}
|
|
|
|
static bool
|
|
nvptx_close_device (struct ptx_device *ptx_dev)
|
|
{
|
|
if (!ptx_dev)
|
|
return true;
|
|
|
|
for (struct ptx_free_block *b = ptx_dev->free_blocks; b;)
|
|
{
|
|
struct ptx_free_block *b_next = b->next;
|
|
CUDA_CALL (cuMemFree, (CUdeviceptr) b->ptr);
|
|
free (b);
|
|
b = b_next;
|
|
}
|
|
|
|
pthread_mutex_destroy (&ptx_dev->free_blocks_lock);
|
|
pthread_mutex_destroy (&ptx_dev->image_lock);
|
|
|
|
if (!ptx_dev->ctx_shared)
|
|
CUDA_CALL (cuCtxDestroy, ptx_dev->ctx);
|
|
|
|
free (ptx_dev);
|
|
return true;
|
|
}
|
|
|
|
static int
|
|
nvptx_get_num_devices (void)
|
|
{
|
|
int n;
|
|
|
|
/* PR libgomp/65099: Currently, we only support offloading in 64-bit
|
|
configurations. */
|
|
if (sizeof (void *) != 8)
|
|
{
|
|
GOMP_PLUGIN_debug (0, "Disabling nvptx offloading;"
|
|
" only 64-bit configurations are supported\n");
|
|
return 0;
|
|
}
|
|
|
|
/* This function will be called before the plugin has been initialized in
|
|
order to enumerate available devices, but CUDA API routines can't be used
|
|
until cuInit has been called. Just call it now (but don't yet do any
|
|
further initialization). */
|
|
if (instantiated_devices == 0)
|
|
{
|
|
if (!init_cuda_lib ())
|
|
return 0;
|
|
CUresult r = CUDA_CALL_NOCHECK (cuInit, 0);
|
|
/* This is not an error: e.g. we may have CUDA libraries installed but
|
|
no devices available. */
|
|
if (r != CUDA_SUCCESS)
|
|
{
|
|
GOMP_PLUGIN_debug (0, "Disabling nvptx offloading; cuInit: %s\n",
|
|
cuda_error (r));
|
|
return 0;
|
|
}
|
|
}
|
|
|
|
CUDA_CALL_ERET (-1, cuDeviceGetCount, &n);
|
|
return n;
|
|
}
|
|
|
|
static void
|
|
notify_var (const char *var_name, const char *env_var)
|
|
{
|
|
if (env_var == NULL)
|
|
GOMP_PLUGIN_debug (0, "%s: <Not defined>\n", var_name);
|
|
else
|
|
GOMP_PLUGIN_debug (0, "%s: '%s'\n", var_name, env_var);
|
|
}
|
|
|
|
static void
|
|
process_GOMP_NVPTX_JIT (intptr_t *gomp_nvptx_o)
|
|
{
|
|
const char *var_name = "GOMP_NVPTX_JIT";
|
|
const char *env_var = secure_getenv (var_name);
|
|
notify_var (var_name, env_var);
|
|
|
|
if (env_var == NULL)
|
|
return;
|
|
|
|
const char *c = env_var;
|
|
while (*c != '\0')
|
|
{
|
|
while (*c == ' ')
|
|
c++;
|
|
|
|
if (c[0] == '-' && c[1] == 'O'
|
|
&& '0' <= c[2] && c[2] <= '4'
|
|
&& (c[3] == '\0' || c[3] == ' '))
|
|
{
|
|
*gomp_nvptx_o = c[2] - '0';
|
|
c += 3;
|
|
continue;
|
|
}
|
|
|
|
GOMP_PLUGIN_error ("Error parsing %s", var_name);
|
|
break;
|
|
}
|
|
}
|
|
|
|
static bool
|
|
link_ptx (CUmodule *module, const struct targ_ptx_obj *ptx_objs,
|
|
unsigned num_objs)
|
|
{
|
|
CUjit_option opts[7];
|
|
void *optvals[7];
|
|
float elapsed = 0.0;
|
|
char elog[1024];
|
|
char ilog[16384];
|
|
CUlinkState linkstate;
|
|
CUresult r;
|
|
void *linkout;
|
|
size_t linkoutsize __attribute__ ((unused));
|
|
|
|
opts[0] = CU_JIT_WALL_TIME;
|
|
optvals[0] = &elapsed;
|
|
|
|
opts[1] = CU_JIT_INFO_LOG_BUFFER;
|
|
optvals[1] = &ilog[0];
|
|
|
|
opts[2] = CU_JIT_INFO_LOG_BUFFER_SIZE_BYTES;
|
|
optvals[2] = (void *) sizeof ilog;
|
|
|
|
opts[3] = CU_JIT_ERROR_LOG_BUFFER;
|
|
optvals[3] = &elog[0];
|
|
|
|
opts[4] = CU_JIT_ERROR_LOG_BUFFER_SIZE_BYTES;
|
|
optvals[4] = (void *) sizeof elog;
|
|
|
|
opts[5] = CU_JIT_LOG_VERBOSE;
|
|
optvals[5] = (void *) 1;
|
|
|
|
static intptr_t gomp_nvptx_o = -1;
|
|
|
|
static bool init_done = false;
|
|
if (!init_done)
|
|
{
|
|
process_GOMP_NVPTX_JIT (&gomp_nvptx_o);
|
|
init_done = true;
|
|
}
|
|
|
|
int nopts = 6;
|
|
if (gomp_nvptx_o != -1)
|
|
{
|
|
opts[nopts] = CU_JIT_OPTIMIZATION_LEVEL;
|
|
optvals[nopts] = (void *) gomp_nvptx_o;
|
|
nopts++;
|
|
}
|
|
|
|
if (CUDA_CALL_EXISTS (cuLinkCreate_v2))
|
|
CUDA_CALL (cuLinkCreate_v2, nopts, opts, optvals, &linkstate);
|
|
else
|
|
CUDA_CALL (cuLinkCreate, nopts, opts, optvals, &linkstate);
|
|
|
|
for (; num_objs--; ptx_objs++)
|
|
{
|
|
/* cuLinkAddData's 'data' argument erroneously omits the const
|
|
qualifier. */
|
|
GOMP_PLUGIN_debug (0, "Loading:\n---\n%s\n---\n", ptx_objs->code);
|
|
if (CUDA_CALL_EXISTS (cuLinkAddData_v2))
|
|
r = CUDA_CALL_NOCHECK (cuLinkAddData_v2, linkstate, CU_JIT_INPUT_PTX,
|
|
(char *) ptx_objs->code, ptx_objs->size,
|
|
0, 0, 0, 0);
|
|
else
|
|
r = CUDA_CALL_NOCHECK (cuLinkAddData, linkstate, CU_JIT_INPUT_PTX,
|
|
(char *) ptx_objs->code, ptx_objs->size,
|
|
0, 0, 0, 0);
|
|
if (r != CUDA_SUCCESS)
|
|
{
|
|
GOMP_PLUGIN_error ("Link error log %s\n", &elog[0]);
|
|
GOMP_PLUGIN_error ("cuLinkAddData (ptx_code) error: %s",
|
|
cuda_error (r));
|
|
return false;
|
|
}
|
|
}
|
|
|
|
GOMP_PLUGIN_debug (0, "Linking\n");
|
|
r = CUDA_CALL_NOCHECK (cuLinkComplete, linkstate, &linkout, &linkoutsize);
|
|
|
|
GOMP_PLUGIN_debug (0, "Link complete: %fms\n", elapsed);
|
|
GOMP_PLUGIN_debug (0, "Link log %s\n", &ilog[0]);
|
|
|
|
if (r != CUDA_SUCCESS)
|
|
{
|
|
GOMP_PLUGIN_error ("cuLinkComplete error: %s", cuda_error (r));
|
|
return false;
|
|
}
|
|
|
|
CUDA_CALL (cuModuleLoadData, module, linkout);
|
|
CUDA_CALL (cuLinkDestroy, linkstate);
|
|
return true;
|
|
}
|
|
|
|
static void
|
|
nvptx_exec (void (*fn), size_t mapnum, void **hostaddrs, void **devaddrs,
|
|
unsigned *dims, void *targ_mem_desc,
|
|
CUdeviceptr dp, CUstream stream)
|
|
{
|
|
struct targ_fn_descriptor *targ_fn = (struct targ_fn_descriptor *) fn;
|
|
CUfunction function;
|
|
int i;
|
|
void *kargs[1];
|
|
struct nvptx_thread *nvthd = nvptx_thread ();
|
|
int warp_size = nvthd->ptx_dev->warp_size;
|
|
|
|
function = targ_fn->fn;
|
|
|
|
/* Initialize the launch dimensions. Typically this is constant,
|
|
provided by the device compiler, but we must permit runtime
|
|
values. */
|
|
int seen_zero = 0;
|
|
for (i = 0; i != GOMP_DIM_MAX; i++)
|
|
{
|
|
if (targ_fn->launch->dim[i])
|
|
dims[i] = targ_fn->launch->dim[i];
|
|
if (!dims[i])
|
|
seen_zero = 1;
|
|
}
|
|
|
|
if (seen_zero)
|
|
{
|
|
pthread_mutex_lock (&ptx_dev_lock);
|
|
|
|
static int gomp_openacc_dims[GOMP_DIM_MAX];
|
|
if (!gomp_openacc_dims[0])
|
|
{
|
|
/* See if the user provided GOMP_OPENACC_DIM environment
|
|
variable to specify runtime defaults. */
|
|
for (int i = 0; i < GOMP_DIM_MAX; ++i)
|
|
gomp_openacc_dims[i] = GOMP_PLUGIN_acc_default_dim (i);
|
|
}
|
|
|
|
if (!nvthd->ptx_dev->default_dims[0])
|
|
{
|
|
int default_dims[GOMP_DIM_MAX];
|
|
for (int i = 0; i < GOMP_DIM_MAX; ++i)
|
|
default_dims[i] = gomp_openacc_dims[i];
|
|
|
|
int gang, worker, vector;
|
|
{
|
|
int block_size = nvthd->ptx_dev->max_threads_per_block;
|
|
int cpu_size = nvthd->ptx_dev->max_threads_per_multiprocessor;
|
|
int dev_size = nvthd->ptx_dev->num_sms;
|
|
GOMP_PLUGIN_debug (0, " warp_size=%d, block_size=%d,"
|
|
" dev_size=%d, cpu_size=%d\n",
|
|
warp_size, block_size, dev_size, cpu_size);
|
|
|
|
gang = (cpu_size / block_size) * dev_size;
|
|
worker = block_size / warp_size;
|
|
vector = warp_size;
|
|
}
|
|
|
|
/* There is no upper bound on the gang size. The best size
|
|
matches the hardware configuration. Logical gangs are
|
|
scheduled onto physical hardware. To maximize usage, we
|
|
should guess a large number. */
|
|
if (default_dims[GOMP_DIM_GANG] < 1)
|
|
default_dims[GOMP_DIM_GANG] = gang ? gang : 1024;
|
|
/* The worker size must not exceed the hardware. */
|
|
if (default_dims[GOMP_DIM_WORKER] < 1
|
|
|| (default_dims[GOMP_DIM_WORKER] > worker && gang))
|
|
default_dims[GOMP_DIM_WORKER] = worker;
|
|
/* The vector size must exactly match the hardware. */
|
|
if (default_dims[GOMP_DIM_VECTOR] < 1
|
|
|| (default_dims[GOMP_DIM_VECTOR] != vector && gang))
|
|
default_dims[GOMP_DIM_VECTOR] = vector;
|
|
|
|
GOMP_PLUGIN_debug (0, " default dimensions [%d,%d,%d]\n",
|
|
default_dims[GOMP_DIM_GANG],
|
|
default_dims[GOMP_DIM_WORKER],
|
|
default_dims[GOMP_DIM_VECTOR]);
|
|
|
|
for (i = 0; i != GOMP_DIM_MAX; i++)
|
|
nvthd->ptx_dev->default_dims[i] = default_dims[i];
|
|
}
|
|
pthread_mutex_unlock (&ptx_dev_lock);
|
|
|
|
{
|
|
bool default_dim_p[GOMP_DIM_MAX];
|
|
for (i = 0; i != GOMP_DIM_MAX; i++)
|
|
default_dim_p[i] = !dims[i];
|
|
|
|
if (!CUDA_CALL_EXISTS (cuOccupancyMaxPotentialBlockSize))
|
|
{
|
|
for (i = 0; i != GOMP_DIM_MAX; i++)
|
|
if (default_dim_p[i])
|
|
dims[i] = nvthd->ptx_dev->default_dims[i];
|
|
|
|
if (default_dim_p[GOMP_DIM_VECTOR])
|
|
dims[GOMP_DIM_VECTOR]
|
|
= MIN (dims[GOMP_DIM_VECTOR],
|
|
(targ_fn->max_threads_per_block / warp_size
|
|
* warp_size));
|
|
|
|
if (default_dim_p[GOMP_DIM_WORKER])
|
|
dims[GOMP_DIM_WORKER]
|
|
= MIN (dims[GOMP_DIM_WORKER],
|
|
targ_fn->max_threads_per_block / dims[GOMP_DIM_VECTOR]);
|
|
}
|
|
else
|
|
{
|
|
/* Handle the case that the compiler allows the runtime to choose
|
|
the vector-length conservatively, by ignoring
|
|
gomp_openacc_dims[GOMP_DIM_VECTOR]. TODO: actually handle
|
|
it. */
|
|
int vectors = 0;
|
|
/* TODO: limit gomp_openacc_dims[GOMP_DIM_WORKER] such that that
|
|
gomp_openacc_dims[GOMP_DIM_WORKER] * actual_vectors does not
|
|
exceed targ_fn->max_threads_per_block. */
|
|
int workers = gomp_openacc_dims[GOMP_DIM_WORKER];
|
|
int gangs = gomp_openacc_dims[GOMP_DIM_GANG];
|
|
int grids, blocks;
|
|
|
|
CUDA_CALL_ASSERT (cuOccupancyMaxPotentialBlockSize, &grids,
|
|
&blocks, function, NULL, 0,
|
|
dims[GOMP_DIM_WORKER] * dims[GOMP_DIM_VECTOR]);
|
|
GOMP_PLUGIN_debug (0, "cuOccupancyMaxPotentialBlockSize: "
|
|
"grid = %d, block = %d\n", grids, blocks);
|
|
|
|
/* Keep the num_gangs proportional to the block size. In
|
|
the case were a block size is limited by shared-memory
|
|
or the register file capacity, the runtime will not
|
|
excessively over assign gangs to the multiprocessor
|
|
units if their state is going to be swapped out even
|
|
more than necessary. The constant factor 2 is there to
|
|
prevent threads from idling when there is insufficient
|
|
work for them. */
|
|
if (gangs == 0)
|
|
gangs = 2 * grids * (blocks / warp_size);
|
|
|
|
if (vectors == 0)
|
|
vectors = warp_size;
|
|
|
|
if (workers == 0)
|
|
{
|
|
int actual_vectors = (default_dim_p[GOMP_DIM_VECTOR]
|
|
? vectors
|
|
: dims[GOMP_DIM_VECTOR]);
|
|
workers = blocks / actual_vectors;
|
|
workers = MAX (workers, 1);
|
|
/* If we need a per-worker barrier ... . */
|
|
if (actual_vectors > 32)
|
|
/* Don't use more barriers than available. */
|
|
workers = MIN (workers, 15);
|
|
}
|
|
|
|
for (i = 0; i != GOMP_DIM_MAX; i++)
|
|
if (default_dim_p[i])
|
|
switch (i)
|
|
{
|
|
case GOMP_DIM_GANG: dims[i] = gangs; break;
|
|
case GOMP_DIM_WORKER: dims[i] = workers; break;
|
|
case GOMP_DIM_VECTOR: dims[i] = vectors; break;
|
|
default: GOMP_PLUGIN_fatal ("invalid dim");
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
/* Check if the accelerator has sufficient hardware resources to
|
|
launch the offloaded kernel. */
|
|
if (dims[GOMP_DIM_WORKER] * dims[GOMP_DIM_VECTOR]
|
|
> targ_fn->max_threads_per_block)
|
|
{
|
|
const char *msg
|
|
= ("The Nvidia accelerator has insufficient resources to launch '%s'"
|
|
" with num_workers = %d and vector_length = %d"
|
|
"; "
|
|
"recompile the program with 'num_workers = x and vector_length = y'"
|
|
" on that offloaded region or '-fopenacc-dim=:x:y' where"
|
|
" x * y <= %d"
|
|
".\n");
|
|
GOMP_PLUGIN_fatal (msg, targ_fn->launch->fn, dims[GOMP_DIM_WORKER],
|
|
dims[GOMP_DIM_VECTOR], targ_fn->max_threads_per_block);
|
|
}
|
|
|
|
/* Check if the accelerator has sufficient barrier resources to
|
|
launch the offloaded kernel. */
|
|
if (dims[GOMP_DIM_WORKER] > 15 && dims[GOMP_DIM_VECTOR] > 32)
|
|
{
|
|
const char *msg
|
|
= ("The Nvidia accelerator has insufficient barrier resources to launch"
|
|
" '%s' with num_workers = %d and vector_length = %d"
|
|
"; "
|
|
"recompile the program with 'num_workers = x' on that offloaded"
|
|
" region or '-fopenacc-dim=:x:' where x <= 15"
|
|
"; "
|
|
"or, recompile the program with 'vector_length = 32' on that"
|
|
" offloaded region or '-fopenacc-dim=::32'"
|
|
".\n");
|
|
GOMP_PLUGIN_fatal (msg, targ_fn->launch->fn, dims[GOMP_DIM_WORKER],
|
|
dims[GOMP_DIM_VECTOR]);
|
|
}
|
|
|
|
GOMP_PLUGIN_debug (0, " %s: kernel %s: launch"
|
|
" gangs=%u, workers=%u, vectors=%u\n",
|
|
__FUNCTION__, targ_fn->launch->fn, dims[GOMP_DIM_GANG],
|
|
dims[GOMP_DIM_WORKER], dims[GOMP_DIM_VECTOR]);
|
|
|
|
// OpenACC CUDA
|
|
//
|
|
// num_gangs nctaid.x
|
|
// num_workers ntid.y
|
|
// vector length ntid.x
|
|
|
|
struct goacc_thread *thr = GOMP_PLUGIN_goacc_thread ();
|
|
acc_prof_info *prof_info = thr->prof_info;
|
|
acc_event_info enqueue_launch_event_info;
|
|
acc_api_info *api_info = thr->api_info;
|
|
bool profiling_p = __builtin_expect (prof_info != NULL, false);
|
|
if (profiling_p)
|
|
{
|
|
prof_info->event_type = acc_ev_enqueue_launch_start;
|
|
|
|
enqueue_launch_event_info.launch_event.event_type
|
|
= prof_info->event_type;
|
|
enqueue_launch_event_info.launch_event.valid_bytes
|
|
= _ACC_LAUNCH_EVENT_INFO_VALID_BYTES;
|
|
enqueue_launch_event_info.launch_event.parent_construct
|
|
= acc_construct_parallel;
|
|
enqueue_launch_event_info.launch_event.implicit = 1;
|
|
enqueue_launch_event_info.launch_event.tool_info = NULL;
|
|
enqueue_launch_event_info.launch_event.kernel_name = targ_fn->launch->fn;
|
|
enqueue_launch_event_info.launch_event.num_gangs
|
|
= dims[GOMP_DIM_GANG];
|
|
enqueue_launch_event_info.launch_event.num_workers
|
|
= dims[GOMP_DIM_WORKER];
|
|
enqueue_launch_event_info.launch_event.vector_length
|
|
= dims[GOMP_DIM_VECTOR];
|
|
|
|
api_info->device_api = acc_device_api_cuda;
|
|
|
|
GOMP_PLUGIN_goacc_profiling_dispatch (prof_info, &enqueue_launch_event_info,
|
|
api_info);
|
|
}
|
|
|
|
kargs[0] = &dp;
|
|
CUDA_CALL_ASSERT (cuLaunchKernel, function,
|
|
dims[GOMP_DIM_GANG], 1, 1,
|
|
dims[GOMP_DIM_VECTOR], dims[GOMP_DIM_WORKER], 1,
|
|
0, stream, kargs, 0);
|
|
|
|
if (profiling_p)
|
|
{
|
|
prof_info->event_type = acc_ev_enqueue_launch_end;
|
|
enqueue_launch_event_info.launch_event.event_type
|
|
= prof_info->event_type;
|
|
GOMP_PLUGIN_goacc_profiling_dispatch (prof_info, &enqueue_launch_event_info,
|
|
api_info);
|
|
}
|
|
|
|
GOMP_PLUGIN_debug (0, " %s: kernel %s: finished\n", __FUNCTION__,
|
|
targ_fn->launch->fn);
|
|
}
|
|
|
|
void * openacc_get_current_cuda_context (void);
|
|
|
|
static void
|
|
goacc_profiling_acc_ev_alloc (struct goacc_thread *thr, void *dp, size_t s)
|
|
{
|
|
acc_prof_info *prof_info = thr->prof_info;
|
|
acc_event_info data_event_info;
|
|
acc_api_info *api_info = thr->api_info;
|
|
|
|
prof_info->event_type = acc_ev_alloc;
|
|
|
|
data_event_info.data_event.event_type = prof_info->event_type;
|
|
data_event_info.data_event.valid_bytes = _ACC_DATA_EVENT_INFO_VALID_BYTES;
|
|
data_event_info.data_event.parent_construct = acc_construct_parallel;
|
|
data_event_info.data_event.implicit = 1;
|
|
data_event_info.data_event.tool_info = NULL;
|
|
data_event_info.data_event.var_name = NULL;
|
|
data_event_info.data_event.bytes = s;
|
|
data_event_info.data_event.host_ptr = NULL;
|
|
data_event_info.data_event.device_ptr = dp;
|
|
|
|
api_info->device_api = acc_device_api_cuda;
|
|
|
|
GOMP_PLUGIN_goacc_profiling_dispatch (prof_info, &data_event_info, api_info);
|
|
}
|
|
|
|
static void *
|
|
nvptx_alloc (size_t s)
|
|
{
|
|
CUdeviceptr d;
|
|
|
|
CUDA_CALL_ERET (NULL, cuMemAlloc, &d, s);
|
|
struct goacc_thread *thr = GOMP_PLUGIN_goacc_thread ();
|
|
bool profiling_p
|
|
= __builtin_expect (thr != NULL && thr->prof_info != NULL, false);
|
|
if (profiling_p)
|
|
goacc_profiling_acc_ev_alloc (thr, (void *) d, s);
|
|
|
|
return (void *) d;
|
|
}
|
|
|
|
static void
|
|
goacc_profiling_acc_ev_free (struct goacc_thread *thr, void *p)
|
|
{
|
|
acc_prof_info *prof_info = thr->prof_info;
|
|
acc_event_info data_event_info;
|
|
acc_api_info *api_info = thr->api_info;
|
|
|
|
prof_info->event_type = acc_ev_free;
|
|
|
|
data_event_info.data_event.event_type = prof_info->event_type;
|
|
data_event_info.data_event.valid_bytes = _ACC_DATA_EVENT_INFO_VALID_BYTES;
|
|
data_event_info.data_event.parent_construct = acc_construct_parallel;
|
|
data_event_info.data_event.implicit = 1;
|
|
data_event_info.data_event.tool_info = NULL;
|
|
data_event_info.data_event.var_name = NULL;
|
|
data_event_info.data_event.bytes = -1;
|
|
data_event_info.data_event.host_ptr = NULL;
|
|
data_event_info.data_event.device_ptr = p;
|
|
|
|
api_info->device_api = acc_device_api_cuda;
|
|
|
|
GOMP_PLUGIN_goacc_profiling_dispatch (prof_info, &data_event_info, api_info);
|
|
}
|
|
|
|
static bool
|
|
nvptx_free (void *p, struct ptx_device *ptx_dev)
|
|
{
|
|
/* Assume callback context if this is null. */
|
|
if (GOMP_PLUGIN_acc_thread () == NULL)
|
|
{
|
|
struct ptx_free_block *n
|
|
= GOMP_PLUGIN_malloc (sizeof (struct ptx_free_block));
|
|
n->ptr = p;
|
|
pthread_mutex_lock (&ptx_dev->free_blocks_lock);
|
|
n->next = ptx_dev->free_blocks;
|
|
ptx_dev->free_blocks = n;
|
|
pthread_mutex_unlock (&ptx_dev->free_blocks_lock);
|
|
return true;
|
|
}
|
|
|
|
CUdeviceptr pb;
|
|
size_t ps;
|
|
|
|
CUDA_CALL (cuMemGetAddressRange, &pb, &ps, (CUdeviceptr) p);
|
|
if ((CUdeviceptr) p != pb)
|
|
{
|
|
GOMP_PLUGIN_error ("invalid device address");
|
|
return false;
|
|
}
|
|
|
|
CUDA_CALL (cuMemFree, (CUdeviceptr) p);
|
|
struct goacc_thread *thr = GOMP_PLUGIN_goacc_thread ();
|
|
bool profiling_p
|
|
= __builtin_expect (thr != NULL && thr->prof_info != NULL, false);
|
|
if (profiling_p)
|
|
goacc_profiling_acc_ev_free (thr, p);
|
|
|
|
return true;
|
|
}
|
|
|
|
static void *
|
|
nvptx_get_current_cuda_device (void)
|
|
{
|
|
struct nvptx_thread *nvthd = nvptx_thread ();
|
|
|
|
if (!nvthd || !nvthd->ptx_dev)
|
|
return NULL;
|
|
|
|
return &nvthd->ptx_dev->dev;
|
|
}
|
|
|
|
static void *
|
|
nvptx_get_current_cuda_context (void)
|
|
{
|
|
struct nvptx_thread *nvthd = nvptx_thread ();
|
|
|
|
if (!nvthd || !nvthd->ptx_dev)
|
|
return NULL;
|
|
|
|
return nvthd->ptx_dev->ctx;
|
|
}
|
|
|
|
/* Plugin entry points. */
|
|
|
|
const char *
|
|
GOMP_OFFLOAD_get_name (void)
|
|
{
|
|
return "nvptx";
|
|
}
|
|
|
|
unsigned int
|
|
GOMP_OFFLOAD_get_caps (void)
|
|
{
|
|
return GOMP_OFFLOAD_CAP_OPENACC_200 | GOMP_OFFLOAD_CAP_OPENMP_400;
|
|
}
|
|
|
|
int
|
|
GOMP_OFFLOAD_get_type (void)
|
|
{
|
|
return OFFLOAD_TARGET_TYPE_NVIDIA_PTX;
|
|
}
|
|
|
|
int
|
|
GOMP_OFFLOAD_get_num_devices (void)
|
|
{
|
|
return nvptx_get_num_devices ();
|
|
}
|
|
|
|
union gomp_device_property_value
|
|
GOMP_OFFLOAD_get_property (int n, int prop)
|
|
{
|
|
union gomp_device_property_value propval = { .val = 0 };
|
|
|
|
pthread_mutex_lock (&ptx_dev_lock);
|
|
|
|
if (n >= nvptx_get_num_devices () || n < 0 || ptx_devices[n] == NULL)
|
|
{
|
|
pthread_mutex_unlock (&ptx_dev_lock);
|
|
return propval;
|
|
}
|
|
|
|
struct ptx_device *ptx_dev = ptx_devices[n];
|
|
switch (prop)
|
|
{
|
|
case GOMP_DEVICE_PROPERTY_MEMORY:
|
|
{
|
|
size_t total_mem;
|
|
|
|
CUDA_CALL_ERET (propval, cuDeviceTotalMem, &total_mem, ptx_dev->dev);
|
|
propval.val = total_mem;
|
|
}
|
|
break;
|
|
case GOMP_DEVICE_PROPERTY_FREE_MEMORY:
|
|
{
|
|
size_t total_mem;
|
|
size_t free_mem;
|
|
CUdevice ctxdev;
|
|
|
|
CUDA_CALL_ERET (propval, cuCtxGetDevice, &ctxdev);
|
|
if (ptx_dev->dev == ctxdev)
|
|
CUDA_CALL_ERET (propval, cuMemGetInfo, &free_mem, &total_mem);
|
|
else if (ptx_dev->ctx)
|
|
{
|
|
CUcontext old_ctx;
|
|
|
|
CUDA_CALL_ERET (propval, cuCtxPushCurrent, ptx_dev->ctx);
|
|
CUDA_CALL_ERET (propval, cuMemGetInfo, &free_mem, &total_mem);
|
|
CUDA_CALL_ASSERT (cuCtxPopCurrent, &old_ctx);
|
|
}
|
|
else
|
|
{
|
|
CUcontext new_ctx;
|
|
|
|
CUDA_CALL_ERET (propval, cuCtxCreate, &new_ctx, CU_CTX_SCHED_AUTO,
|
|
ptx_dev->dev);
|
|
CUDA_CALL_ERET (propval, cuMemGetInfo, &free_mem, &total_mem);
|
|
CUDA_CALL_ASSERT (cuCtxDestroy, new_ctx);
|
|
}
|
|
propval.val = free_mem;
|
|
}
|
|
break;
|
|
case GOMP_DEVICE_PROPERTY_NAME:
|
|
propval.ptr = ptx_dev->name;
|
|
break;
|
|
case GOMP_DEVICE_PROPERTY_VENDOR:
|
|
propval.ptr = "Nvidia";
|
|
break;
|
|
case GOMP_DEVICE_PROPERTY_DRIVER:
|
|
propval.ptr = cuda_driver_version_s;
|
|
break;
|
|
}
|
|
|
|
pthread_mutex_unlock (&ptx_dev_lock);
|
|
return propval;
|
|
}
|
|
|
|
bool
|
|
GOMP_OFFLOAD_init_device (int n)
|
|
{
|
|
struct ptx_device *dev;
|
|
|
|
pthread_mutex_lock (&ptx_dev_lock);
|
|
|
|
if (!nvptx_init () || ptx_devices[n] != NULL)
|
|
{
|
|
pthread_mutex_unlock (&ptx_dev_lock);
|
|
return false;
|
|
}
|
|
|
|
dev = nvptx_open_device (n);
|
|
if (dev)
|
|
{
|
|
ptx_devices[n] = dev;
|
|
instantiated_devices++;
|
|
}
|
|
|
|
pthread_mutex_unlock (&ptx_dev_lock);
|
|
|
|
return dev != NULL;
|
|
}
|
|
|
|
bool
|
|
GOMP_OFFLOAD_fini_device (int n)
|
|
{
|
|
pthread_mutex_lock (&ptx_dev_lock);
|
|
|
|
if (ptx_devices[n] != NULL)
|
|
{
|
|
if (!nvptx_attach_host_thread_to_device (n)
|
|
|| !nvptx_close_device (ptx_devices[n]))
|
|
{
|
|
pthread_mutex_unlock (&ptx_dev_lock);
|
|
return false;
|
|
}
|
|
ptx_devices[n] = NULL;
|
|
instantiated_devices--;
|
|
}
|
|
|
|
if (instantiated_devices == 0)
|
|
{
|
|
free (ptx_devices);
|
|
ptx_devices = NULL;
|
|
}
|
|
|
|
pthread_mutex_unlock (&ptx_dev_lock);
|
|
return true;
|
|
}
|
|
|
|
/* Return the libgomp version number we're compatible with. There is
|
|
no requirement for cross-version compatibility. */
|
|
|
|
unsigned
|
|
GOMP_OFFLOAD_version (void)
|
|
{
|
|
return GOMP_VERSION;
|
|
}
|
|
|
|
/* Initialize __nvptx_clocktick, if present in MODULE. */
|
|
|
|
static void
|
|
nvptx_set_clocktick (CUmodule module, struct ptx_device *dev)
|
|
{
|
|
CUdeviceptr dptr;
|
|
CUresult r = CUDA_CALL_NOCHECK (cuModuleGetGlobal, &dptr, NULL,
|
|
module, "__nvptx_clocktick");
|
|
if (r == CUDA_ERROR_NOT_FOUND)
|
|
return;
|
|
if (r != CUDA_SUCCESS)
|
|
GOMP_PLUGIN_fatal ("cuModuleGetGlobal error: %s", cuda_error (r));
|
|
double __nvptx_clocktick = 1e-3 / dev->clock_khz;
|
|
r = CUDA_CALL_NOCHECK (cuMemcpyHtoD, dptr, &__nvptx_clocktick,
|
|
sizeof (__nvptx_clocktick));
|
|
if (r != CUDA_SUCCESS)
|
|
GOMP_PLUGIN_fatal ("cuMemcpyHtoD error: %s", cuda_error (r));
|
|
}
|
|
|
|
/* Load the (partial) program described by TARGET_DATA to device
|
|
number ORD. Allocate and return TARGET_TABLE. */
|
|
|
|
int
|
|
GOMP_OFFLOAD_load_image (int ord, unsigned version, const void *target_data,
|
|
struct addr_pair **target_table)
|
|
{
|
|
CUmodule module;
|
|
const char *const *var_names;
|
|
const struct targ_fn_launch *fn_descs;
|
|
unsigned int fn_entries, var_entries, i, j;
|
|
struct targ_fn_descriptor *targ_fns;
|
|
struct addr_pair *targ_tbl;
|
|
const nvptx_tdata_t *img_header = (const nvptx_tdata_t *) target_data;
|
|
struct ptx_image_data *new_image;
|
|
struct ptx_device *dev;
|
|
|
|
if (GOMP_VERSION_DEV (version) > GOMP_VERSION_NVIDIA_PTX)
|
|
{
|
|
GOMP_PLUGIN_error ("Offload data incompatible with PTX plugin"
|
|
" (expected %u, received %u)",
|
|
GOMP_VERSION_NVIDIA_PTX, GOMP_VERSION_DEV (version));
|
|
return -1;
|
|
}
|
|
|
|
if (!nvptx_attach_host_thread_to_device (ord)
|
|
|| !link_ptx (&module, img_header->ptx_objs, img_header->ptx_num))
|
|
return -1;
|
|
|
|
dev = ptx_devices[ord];
|
|
|
|
/* The mkoffload utility emits a struct of pointers/integers at the
|
|
start of each offload image. The array of kernel names and the
|
|
functions addresses form a one-to-one correspondence. */
|
|
|
|
var_entries = img_header->var_num;
|
|
var_names = img_header->var_names;
|
|
fn_entries = img_header->fn_num;
|
|
fn_descs = img_header->fn_descs;
|
|
|
|
targ_tbl = GOMP_PLUGIN_malloc (sizeof (struct addr_pair)
|
|
* (fn_entries + var_entries));
|
|
targ_fns = GOMP_PLUGIN_malloc (sizeof (struct targ_fn_descriptor)
|
|
* fn_entries);
|
|
|
|
*target_table = targ_tbl;
|
|
|
|
new_image = GOMP_PLUGIN_malloc (sizeof (struct ptx_image_data));
|
|
new_image->target_data = target_data;
|
|
new_image->module = module;
|
|
new_image->fns = targ_fns;
|
|
|
|
pthread_mutex_lock (&dev->image_lock);
|
|
new_image->next = dev->images;
|
|
dev->images = new_image;
|
|
pthread_mutex_unlock (&dev->image_lock);
|
|
|
|
for (i = 0; i < fn_entries; i++, targ_fns++, targ_tbl++)
|
|
{
|
|
CUfunction function;
|
|
int nregs, mthrs;
|
|
|
|
CUDA_CALL_ERET (-1, cuModuleGetFunction, &function, module,
|
|
fn_descs[i].fn);
|
|
CUDA_CALL_ERET (-1, cuFuncGetAttribute, &nregs,
|
|
CU_FUNC_ATTRIBUTE_NUM_REGS, function);
|
|
CUDA_CALL_ERET (-1, cuFuncGetAttribute, &mthrs,
|
|
CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK, function);
|
|
|
|
targ_fns->fn = function;
|
|
targ_fns->launch = &fn_descs[i];
|
|
targ_fns->regs_per_thread = nregs;
|
|
targ_fns->max_threads_per_block = mthrs;
|
|
|
|
targ_tbl->start = (uintptr_t) targ_fns;
|
|
targ_tbl->end = targ_tbl->start + 1;
|
|
}
|
|
|
|
for (j = 0; j < var_entries; j++, targ_tbl++)
|
|
{
|
|
CUdeviceptr var;
|
|
size_t bytes;
|
|
|
|
CUDA_CALL_ERET (-1, cuModuleGetGlobal,
|
|
&var, &bytes, module, var_names[j]);
|
|
|
|
targ_tbl->start = (uintptr_t) var;
|
|
targ_tbl->end = targ_tbl->start + bytes;
|
|
}
|
|
|
|
nvptx_set_clocktick (module, dev);
|
|
|
|
return fn_entries + var_entries;
|
|
}
|
|
|
|
/* Unload the program described by TARGET_DATA. DEV_DATA is the
|
|
function descriptors allocated by G_O_load_image. */
|
|
|
|
bool
|
|
GOMP_OFFLOAD_unload_image (int ord, unsigned version, const void *target_data)
|
|
{
|
|
struct ptx_image_data *image, **prev_p;
|
|
struct ptx_device *dev = ptx_devices[ord];
|
|
|
|
if (GOMP_VERSION_DEV (version) > GOMP_VERSION_NVIDIA_PTX)
|
|
{
|
|
GOMP_PLUGIN_error ("Offload data incompatible with PTX plugin"
|
|
" (expected %u, received %u)",
|
|
GOMP_VERSION_NVIDIA_PTX, GOMP_VERSION_DEV (version));
|
|
return false;
|
|
}
|
|
|
|
bool ret = true;
|
|
pthread_mutex_lock (&dev->image_lock);
|
|
for (prev_p = &dev->images; (image = *prev_p) != 0; prev_p = &image->next)
|
|
if (image->target_data == target_data)
|
|
{
|
|
*prev_p = image->next;
|
|
if (CUDA_CALL_NOCHECK (cuModuleUnload, image->module) != CUDA_SUCCESS)
|
|
ret = false;
|
|
free (image->fns);
|
|
free (image);
|
|
break;
|
|
}
|
|
pthread_mutex_unlock (&dev->image_lock);
|
|
return ret;
|
|
}
|
|
|
|
void *
|
|
GOMP_OFFLOAD_alloc (int ord, size_t size)
|
|
{
|
|
if (!nvptx_attach_host_thread_to_device (ord))
|
|
return NULL;
|
|
|
|
struct ptx_device *ptx_dev = ptx_devices[ord];
|
|
struct ptx_free_block *blocks, *tmp;
|
|
|
|
pthread_mutex_lock (&ptx_dev->free_blocks_lock);
|
|
blocks = ptx_dev->free_blocks;
|
|
ptx_dev->free_blocks = NULL;
|
|
pthread_mutex_unlock (&ptx_dev->free_blocks_lock);
|
|
|
|
while (blocks)
|
|
{
|
|
tmp = blocks->next;
|
|
nvptx_free (blocks->ptr, ptx_dev);
|
|
free (blocks);
|
|
blocks = tmp;
|
|
}
|
|
|
|
return nvptx_alloc (size);
|
|
}
|
|
|
|
bool
|
|
GOMP_OFFLOAD_free (int ord, void *ptr)
|
|
{
|
|
return (nvptx_attach_host_thread_to_device (ord)
|
|
&& nvptx_free (ptr, ptx_devices[ord]));
|
|
}
|
|
|
|
void
|
|
GOMP_OFFLOAD_openacc_exec (void (*fn) (void *), size_t mapnum,
|
|
void **hostaddrs, void **devaddrs,
|
|
unsigned *dims, void *targ_mem_desc)
|
|
{
|
|
GOMP_PLUGIN_debug (0, " %s: prepare mappings\n", __FUNCTION__);
|
|
|
|
struct goacc_thread *thr = GOMP_PLUGIN_goacc_thread ();
|
|
acc_prof_info *prof_info = thr->prof_info;
|
|
acc_event_info data_event_info;
|
|
acc_api_info *api_info = thr->api_info;
|
|
bool profiling_p = __builtin_expect (prof_info != NULL, false);
|
|
|
|
void **hp = NULL;
|
|
CUdeviceptr dp = 0;
|
|
|
|
if (mapnum > 0)
|
|
{
|
|
size_t s = mapnum * sizeof (void *);
|
|
hp = alloca (s);
|
|
for (int i = 0; i < mapnum; i++)
|
|
hp[i] = (devaddrs[i] ? devaddrs[i] : hostaddrs[i]);
|
|
CUDA_CALL_ASSERT (cuMemAlloc, &dp, s);
|
|
if (profiling_p)
|
|
goacc_profiling_acc_ev_alloc (thr, (void *) dp, s);
|
|
}
|
|
|
|
/* Copy the (device) pointers to arguments to the device (dp and hp might in
|
|
fact have the same value on a unified-memory system). */
|
|
if (mapnum > 0)
|
|
{
|
|
if (profiling_p)
|
|
{
|
|
prof_info->event_type = acc_ev_enqueue_upload_start;
|
|
|
|
data_event_info.data_event.event_type = prof_info->event_type;
|
|
data_event_info.data_event.valid_bytes
|
|
= _ACC_DATA_EVENT_INFO_VALID_BYTES;
|
|
data_event_info.data_event.parent_construct
|
|
= acc_construct_parallel;
|
|
data_event_info.data_event.implicit = 1; /* Always implicit. */
|
|
data_event_info.data_event.tool_info = NULL;
|
|
data_event_info.data_event.var_name = NULL;
|
|
data_event_info.data_event.bytes = mapnum * sizeof (void *);
|
|
data_event_info.data_event.host_ptr = hp;
|
|
data_event_info.data_event.device_ptr = (const void *) dp;
|
|
|
|
api_info->device_api = acc_device_api_cuda;
|
|
|
|
GOMP_PLUGIN_goacc_profiling_dispatch (prof_info, &data_event_info,
|
|
api_info);
|
|
}
|
|
CUDA_CALL_ASSERT (cuMemcpyHtoD, dp, (void *) hp,
|
|
mapnum * sizeof (void *));
|
|
if (profiling_p)
|
|
{
|
|
prof_info->event_type = acc_ev_enqueue_upload_end;
|
|
data_event_info.data_event.event_type = prof_info->event_type;
|
|
GOMP_PLUGIN_goacc_profiling_dispatch (prof_info, &data_event_info,
|
|
api_info);
|
|
}
|
|
}
|
|
|
|
nvptx_exec (fn, mapnum, hostaddrs, devaddrs, dims, targ_mem_desc,
|
|
dp, NULL);
|
|
|
|
CUresult r = CUDA_CALL_NOCHECK (cuStreamSynchronize, NULL);
|
|
const char *maybe_abort_msg = "(perhaps abort was called)";
|
|
if (r == CUDA_ERROR_LAUNCH_FAILED)
|
|
GOMP_PLUGIN_fatal ("cuStreamSynchronize error: %s %s\n", cuda_error (r),
|
|
maybe_abort_msg);
|
|
else if (r != CUDA_SUCCESS)
|
|
GOMP_PLUGIN_fatal ("cuStreamSynchronize error: %s", cuda_error (r));
|
|
|
|
CUDA_CALL_ASSERT (cuMemFree, dp);
|
|
if (profiling_p)
|
|
goacc_profiling_acc_ev_free (thr, (void *) dp);
|
|
}
|
|
|
|
static void
|
|
cuda_free_argmem (void *ptr)
|
|
{
|
|
void **block = (void **) ptr;
|
|
nvptx_free (block[0], (struct ptx_device *) block[1]);
|
|
free (block);
|
|
}
|
|
|
|
void
|
|
GOMP_OFFLOAD_openacc_async_exec (void (*fn) (void *), size_t mapnum,
|
|
void **hostaddrs, void **devaddrs,
|
|
unsigned *dims, void *targ_mem_desc,
|
|
struct goacc_asyncqueue *aq)
|
|
{
|
|
GOMP_PLUGIN_debug (0, " %s: prepare mappings\n", __FUNCTION__);
|
|
|
|
struct goacc_thread *thr = GOMP_PLUGIN_goacc_thread ();
|
|
acc_prof_info *prof_info = thr->prof_info;
|
|
acc_event_info data_event_info;
|
|
acc_api_info *api_info = thr->api_info;
|
|
bool profiling_p = __builtin_expect (prof_info != NULL, false);
|
|
|
|
void **hp = NULL;
|
|
CUdeviceptr dp = 0;
|
|
void **block = NULL;
|
|
|
|
if (mapnum > 0)
|
|
{
|
|
size_t s = mapnum * sizeof (void *);
|
|
block = (void **) GOMP_PLUGIN_malloc (2 * sizeof (void *) + s);
|
|
hp = block + 2;
|
|
for (int i = 0; i < mapnum; i++)
|
|
hp[i] = (devaddrs[i] ? devaddrs[i] : hostaddrs[i]);
|
|
CUDA_CALL_ASSERT (cuMemAlloc, &dp, s);
|
|
if (profiling_p)
|
|
goacc_profiling_acc_ev_alloc (thr, (void *) dp, s);
|
|
}
|
|
|
|
/* Copy the (device) pointers to arguments to the device (dp and hp might in
|
|
fact have the same value on a unified-memory system). */
|
|
if (mapnum > 0)
|
|
{
|
|
if (profiling_p)
|
|
{
|
|
prof_info->event_type = acc_ev_enqueue_upload_start;
|
|
|
|
data_event_info.data_event.event_type = prof_info->event_type;
|
|
data_event_info.data_event.valid_bytes
|
|
= _ACC_DATA_EVENT_INFO_VALID_BYTES;
|
|
data_event_info.data_event.parent_construct
|
|
= acc_construct_parallel;
|
|
data_event_info.data_event.implicit = 1; /* Always implicit. */
|
|
data_event_info.data_event.tool_info = NULL;
|
|
data_event_info.data_event.var_name = NULL;
|
|
data_event_info.data_event.bytes = mapnum * sizeof (void *);
|
|
data_event_info.data_event.host_ptr = hp;
|
|
data_event_info.data_event.device_ptr = (const void *) dp;
|
|
|
|
api_info->device_api = acc_device_api_cuda;
|
|
|
|
GOMP_PLUGIN_goacc_profiling_dispatch (prof_info, &data_event_info,
|
|
api_info);
|
|
}
|
|
|
|
CUDA_CALL_ASSERT (cuMemcpyHtoDAsync, dp, (void *) hp,
|
|
mapnum * sizeof (void *), aq->cuda_stream);
|
|
block[0] = (void *) dp;
|
|
|
|
struct nvptx_thread *nvthd =
|
|
(struct nvptx_thread *) GOMP_PLUGIN_acc_thread ();
|
|
block[1] = (void *) nvthd->ptx_dev;
|
|
|
|
if (profiling_p)
|
|
{
|
|
prof_info->event_type = acc_ev_enqueue_upload_end;
|
|
data_event_info.data_event.event_type = prof_info->event_type;
|
|
GOMP_PLUGIN_goacc_profiling_dispatch (prof_info, &data_event_info,
|
|
api_info);
|
|
}
|
|
}
|
|
|
|
nvptx_exec (fn, mapnum, hostaddrs, devaddrs, dims, targ_mem_desc,
|
|
dp, aq->cuda_stream);
|
|
|
|
if (mapnum > 0)
|
|
GOMP_OFFLOAD_openacc_async_queue_callback (aq, cuda_free_argmem, block);
|
|
}
|
|
|
|
void *
|
|
GOMP_OFFLOAD_openacc_create_thread_data (int ord)
|
|
{
|
|
struct ptx_device *ptx_dev;
|
|
struct nvptx_thread *nvthd
|
|
= GOMP_PLUGIN_malloc (sizeof (struct nvptx_thread));
|
|
CUcontext thd_ctx;
|
|
|
|
ptx_dev = ptx_devices[ord];
|
|
|
|
assert (ptx_dev);
|
|
|
|
CUDA_CALL_ASSERT (cuCtxGetCurrent, &thd_ctx);
|
|
|
|
assert (ptx_dev->ctx);
|
|
|
|
if (!thd_ctx)
|
|
CUDA_CALL_ASSERT (cuCtxPushCurrent, ptx_dev->ctx);
|
|
|
|
nvthd->ptx_dev = ptx_dev;
|
|
|
|
return (void *) nvthd;
|
|
}
|
|
|
|
void
|
|
GOMP_OFFLOAD_openacc_destroy_thread_data (void *data)
|
|
{
|
|
free (data);
|
|
}
|
|
|
|
void *
|
|
GOMP_OFFLOAD_openacc_cuda_get_current_device (void)
|
|
{
|
|
return nvptx_get_current_cuda_device ();
|
|
}
|
|
|
|
void *
|
|
GOMP_OFFLOAD_openacc_cuda_get_current_context (void)
|
|
{
|
|
return nvptx_get_current_cuda_context ();
|
|
}
|
|
|
|
/* This returns a CUstream. */
|
|
void *
|
|
GOMP_OFFLOAD_openacc_cuda_get_stream (struct goacc_asyncqueue *aq)
|
|
{
|
|
return (void *) aq->cuda_stream;
|
|
}
|
|
|
|
/* This takes a CUstream. */
|
|
int
|
|
GOMP_OFFLOAD_openacc_cuda_set_stream (struct goacc_asyncqueue *aq, void *stream)
|
|
{
|
|
if (aq->cuda_stream)
|
|
{
|
|
CUDA_CALL_ASSERT (cuStreamSynchronize, aq->cuda_stream);
|
|
CUDA_CALL_ASSERT (cuStreamDestroy, aq->cuda_stream);
|
|
}
|
|
|
|
aq->cuda_stream = (CUstream) stream;
|
|
return 1;
|
|
}
|
|
|
|
struct goacc_asyncqueue *
|
|
GOMP_OFFLOAD_openacc_async_construct (int device __attribute__((unused)))
|
|
{
|
|
CUstream stream = NULL;
|
|
CUDA_CALL_ERET (NULL, cuStreamCreate, &stream, CU_STREAM_DEFAULT);
|
|
|
|
struct goacc_asyncqueue *aq
|
|
= GOMP_PLUGIN_malloc (sizeof (struct goacc_asyncqueue));
|
|
aq->cuda_stream = stream;
|
|
return aq;
|
|
}
|
|
|
|
bool
|
|
GOMP_OFFLOAD_openacc_async_destruct (struct goacc_asyncqueue *aq)
|
|
{
|
|
CUDA_CALL_ERET (false, cuStreamDestroy, aq->cuda_stream);
|
|
free (aq);
|
|
return true;
|
|
}
|
|
|
|
int
|
|
GOMP_OFFLOAD_openacc_async_test (struct goacc_asyncqueue *aq)
|
|
{
|
|
CUresult r = CUDA_CALL_NOCHECK (cuStreamQuery, aq->cuda_stream);
|
|
if (r == CUDA_SUCCESS)
|
|
return 1;
|
|
if (r == CUDA_ERROR_NOT_READY)
|
|
return 0;
|
|
|
|
GOMP_PLUGIN_error ("cuStreamQuery error: %s", cuda_error (r));
|
|
return -1;
|
|
}
|
|
|
|
bool
|
|
GOMP_OFFLOAD_openacc_async_synchronize (struct goacc_asyncqueue *aq)
|
|
{
|
|
CUDA_CALL_ERET (false, cuStreamSynchronize, aq->cuda_stream);
|
|
return true;
|
|
}
|
|
|
|
bool
|
|
GOMP_OFFLOAD_openacc_async_serialize (struct goacc_asyncqueue *aq1,
|
|
struct goacc_asyncqueue *aq2)
|
|
{
|
|
CUevent e;
|
|
CUDA_CALL_ERET (false, cuEventCreate, &e, CU_EVENT_DISABLE_TIMING);
|
|
CUDA_CALL_ERET (false, cuEventRecord, e, aq1->cuda_stream);
|
|
CUDA_CALL_ERET (false, cuStreamWaitEvent, aq2->cuda_stream, e, 0);
|
|
return true;
|
|
}
|
|
|
|
static void
|
|
cuda_callback_wrapper (CUstream stream, CUresult res, void *ptr)
|
|
{
|
|
if (res != CUDA_SUCCESS)
|
|
GOMP_PLUGIN_fatal ("%s error: %s", __FUNCTION__, cuda_error (res));
|
|
struct nvptx_callback *cb = (struct nvptx_callback *) ptr;
|
|
cb->fn (cb->ptr);
|
|
free (ptr);
|
|
}
|
|
|
|
void
|
|
GOMP_OFFLOAD_openacc_async_queue_callback (struct goacc_asyncqueue *aq,
|
|
void (*callback_fn)(void *),
|
|
void *userptr)
|
|
{
|
|
struct nvptx_callback *b = GOMP_PLUGIN_malloc (sizeof (*b));
|
|
b->fn = callback_fn;
|
|
b->ptr = userptr;
|
|
b->aq = aq;
|
|
CUDA_CALL_ASSERT (cuStreamAddCallback, aq->cuda_stream,
|
|
cuda_callback_wrapper, (void *) b, 0);
|
|
}
|
|
|
|
static bool
|
|
cuda_memcpy_sanity_check (const void *h, const void *d, size_t s)
|
|
{
|
|
CUdeviceptr pb;
|
|
size_t ps;
|
|
if (!s)
|
|
return true;
|
|
if (!d)
|
|
{
|
|
GOMP_PLUGIN_error ("invalid device address");
|
|
return false;
|
|
}
|
|
CUDA_CALL (cuMemGetAddressRange, &pb, &ps, (CUdeviceptr) d);
|
|
if (!pb)
|
|
{
|
|
GOMP_PLUGIN_error ("invalid device address");
|
|
return false;
|
|
}
|
|
if (!h)
|
|
{
|
|
GOMP_PLUGIN_error ("invalid host address");
|
|
return false;
|
|
}
|
|
if (d == h)
|
|
{
|
|
GOMP_PLUGIN_error ("invalid host or device address");
|
|
return false;
|
|
}
|
|
if ((void *)(d + s) > (void *)(pb + ps))
|
|
{
|
|
GOMP_PLUGIN_error ("invalid size");
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
bool
|
|
GOMP_OFFLOAD_host2dev (int ord, void *dst, const void *src, size_t n)
|
|
{
|
|
if (!nvptx_attach_host_thread_to_device (ord)
|
|
|| !cuda_memcpy_sanity_check (src, dst, n))
|
|
return false;
|
|
CUDA_CALL (cuMemcpyHtoD, (CUdeviceptr) dst, src, n);
|
|
return true;
|
|
}
|
|
|
|
bool
|
|
GOMP_OFFLOAD_dev2host (int ord, void *dst, const void *src, size_t n)
|
|
{
|
|
if (!nvptx_attach_host_thread_to_device (ord)
|
|
|| !cuda_memcpy_sanity_check (dst, src, n))
|
|
return false;
|
|
CUDA_CALL (cuMemcpyDtoH, dst, (CUdeviceptr) src, n);
|
|
return true;
|
|
}
|
|
|
|
bool
|
|
GOMP_OFFLOAD_dev2dev (int ord, void *dst, const void *src, size_t n)
|
|
{
|
|
CUDA_CALL (cuMemcpyDtoDAsync, (CUdeviceptr) dst, (CUdeviceptr) src, n, NULL);
|
|
return true;
|
|
}
|
|
|
|
bool
|
|
GOMP_OFFLOAD_openacc_async_host2dev (int ord, void *dst, const void *src,
|
|
size_t n, struct goacc_asyncqueue *aq)
|
|
{
|
|
if (!nvptx_attach_host_thread_to_device (ord)
|
|
|| !cuda_memcpy_sanity_check (src, dst, n))
|
|
return false;
|
|
CUDA_CALL (cuMemcpyHtoDAsync, (CUdeviceptr) dst, src, n, aq->cuda_stream);
|
|
return true;
|
|
}
|
|
|
|
bool
|
|
GOMP_OFFLOAD_openacc_async_dev2host (int ord, void *dst, const void *src,
|
|
size_t n, struct goacc_asyncqueue *aq)
|
|
{
|
|
if (!nvptx_attach_host_thread_to_device (ord)
|
|
|| !cuda_memcpy_sanity_check (dst, src, n))
|
|
return false;
|
|
CUDA_CALL (cuMemcpyDtoHAsync, dst, (CUdeviceptr) src, n, aq->cuda_stream);
|
|
return true;
|
|
}
|
|
|
|
/* Adjust launch dimensions: pick good values for number of blocks and warps
|
|
and ensure that number of warps does not exceed CUDA limits as well as GCC's
|
|
own limits. */
|
|
|
|
static void
|
|
nvptx_adjust_launch_bounds (struct targ_fn_descriptor *fn,
|
|
struct ptx_device *ptx_dev,
|
|
int *teams_p, int *threads_p)
|
|
{
|
|
int max_warps_block = fn->max_threads_per_block / 32;
|
|
/* Maximum 32 warps per block is an implementation limit in NVPTX backend
|
|
and libgcc, which matches documented limit of all GPUs as of 2015. */
|
|
if (max_warps_block > 32)
|
|
max_warps_block = 32;
|
|
if (*threads_p <= 0)
|
|
*threads_p = 8;
|
|
if (*threads_p > max_warps_block)
|
|
*threads_p = max_warps_block;
|
|
|
|
int regs_per_block = fn->regs_per_thread * 32 * *threads_p;
|
|
/* This is an estimate of how many blocks the device can host simultaneously.
|
|
Actual limit, which may be lower, can be queried with "occupancy control"
|
|
driver interface (since CUDA 6.0). */
|
|
int max_blocks = ptx_dev->regs_per_sm / regs_per_block * ptx_dev->num_sms;
|
|
if (*teams_p <= 0 || *teams_p > max_blocks)
|
|
*teams_p = max_blocks;
|
|
}
|
|
|
|
/* Return the size of per-warp stacks (see gcc -msoft-stack) to use for OpenMP
|
|
target regions. */
|
|
|
|
static size_t
|
|
nvptx_stacks_size ()
|
|
{
|
|
return 128 * 1024;
|
|
}
|
|
|
|
/* Return contiguous storage for NUM stacks, each SIZE bytes. */
|
|
|
|
static void *
|
|
nvptx_stacks_alloc (size_t size, int num)
|
|
{
|
|
CUdeviceptr stacks;
|
|
CUresult r = CUDA_CALL_NOCHECK (cuMemAlloc, &stacks, size * num);
|
|
if (r != CUDA_SUCCESS)
|
|
GOMP_PLUGIN_fatal ("cuMemAlloc error: %s", cuda_error (r));
|
|
return (void *) stacks;
|
|
}
|
|
|
|
/* Release storage previously allocated by nvptx_stacks_alloc. */
|
|
|
|
static void
|
|
nvptx_stacks_free (void *p, int num)
|
|
{
|
|
CUresult r = CUDA_CALL_NOCHECK (cuMemFree, (CUdeviceptr) p);
|
|
if (r != CUDA_SUCCESS)
|
|
GOMP_PLUGIN_fatal ("cuMemFree error: %s", cuda_error (r));
|
|
}
|
|
|
|
void
|
|
GOMP_OFFLOAD_run (int ord, void *tgt_fn, void *tgt_vars, void **args)
|
|
{
|
|
CUfunction function = ((struct targ_fn_descriptor *) tgt_fn)->fn;
|
|
CUresult r;
|
|
struct ptx_device *ptx_dev = ptx_devices[ord];
|
|
const char *maybe_abort_msg = "(perhaps abort was called)";
|
|
int teams = 0, threads = 0;
|
|
|
|
if (!args)
|
|
GOMP_PLUGIN_fatal ("No target arguments provided");
|
|
while (*args)
|
|
{
|
|
intptr_t id = (intptr_t) *args++, val;
|
|
if (id & GOMP_TARGET_ARG_SUBSEQUENT_PARAM)
|
|
val = (intptr_t) *args++;
|
|
else
|
|
val = id >> GOMP_TARGET_ARG_VALUE_SHIFT;
|
|
if ((id & GOMP_TARGET_ARG_DEVICE_MASK) != GOMP_TARGET_ARG_DEVICE_ALL)
|
|
continue;
|
|
val = val > INT_MAX ? INT_MAX : val;
|
|
id &= GOMP_TARGET_ARG_ID_MASK;
|
|
if (id == GOMP_TARGET_ARG_NUM_TEAMS)
|
|
teams = val;
|
|
else if (id == GOMP_TARGET_ARG_THREAD_LIMIT)
|
|
threads = val;
|
|
}
|
|
nvptx_adjust_launch_bounds (tgt_fn, ptx_dev, &teams, &threads);
|
|
|
|
size_t stack_size = nvptx_stacks_size ();
|
|
void *stacks = nvptx_stacks_alloc (stack_size, teams * threads);
|
|
void *fn_args[] = {tgt_vars, stacks, (void *) stack_size};
|
|
size_t fn_args_size = sizeof fn_args;
|
|
void *config[] = {
|
|
CU_LAUNCH_PARAM_BUFFER_POINTER, fn_args,
|
|
CU_LAUNCH_PARAM_BUFFER_SIZE, &fn_args_size,
|
|
CU_LAUNCH_PARAM_END
|
|
};
|
|
r = CUDA_CALL_NOCHECK (cuLaunchKernel, function, teams, 1, 1,
|
|
32, threads, 1, 0, NULL, NULL, config);
|
|
if (r != CUDA_SUCCESS)
|
|
GOMP_PLUGIN_fatal ("cuLaunchKernel error: %s", cuda_error (r));
|
|
|
|
r = CUDA_CALL_NOCHECK (cuCtxSynchronize, );
|
|
if (r == CUDA_ERROR_LAUNCH_FAILED)
|
|
GOMP_PLUGIN_fatal ("cuCtxSynchronize error: %s %s\n", cuda_error (r),
|
|
maybe_abort_msg);
|
|
else if (r != CUDA_SUCCESS)
|
|
GOMP_PLUGIN_fatal ("cuCtxSynchronize error: %s", cuda_error (r));
|
|
nvptx_stacks_free (stacks, teams * threads);
|
|
}
|
|
|
|
void
|
|
GOMP_OFFLOAD_async_run (int ord, void *tgt_fn, void *tgt_vars, void **args,
|
|
void *async_data)
|
|
{
|
|
GOMP_PLUGIN_fatal ("GOMP_OFFLOAD_async_run unimplemented");
|
|
}
|