Mercurial > hg > truffle
view src/gpu/ptx/vm/gpu_ptx.cpp @ 13109:58dfd753ada8
fixed regression from recent hsx merge that prevented TypeProfileLevel from being enabled
author | Doug Simon <doug.simon@oracle.com> |
---|---|
date | Fri, 22 Nov 2013 01:40:16 +0100 |
parents | 1a7e7011a341 |
children | 220ed109bf77 |
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/* * Copyright (c) 2013, Oracle and/or its affiliates. All rights reserved. * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. * * This code is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 2 only, as * published by the Free Software Foundation. * * This code is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * version 2 for more details (a copy is included in the LICENSE file that * accompanied this code). * * You should have received a copy of the GNU General Public License version * 2 along with this work; if not, write to the Free Software Foundation, * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. * * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA * or visit www.oracle.com if you need additional information or have any * questions. * */ #include "precompiled.hpp" #include "runtime/javaCalls.hpp" #include "runtime/gpu.hpp" #include "utilities/globalDefinitions.hpp" #include "utilities/ostream.hpp" #include "memory/allocation.hpp" #include "memory/allocation.inline.hpp" #include "ptxKernelArguments.hpp" void * gpu::Ptx::_device_context; int gpu::Ptx::_cu_device = 0; gpu::Ptx::cuda_cu_init_func_t gpu::Ptx::_cuda_cu_init; gpu::Ptx::cuda_cu_ctx_create_func_t gpu::Ptx::_cuda_cu_ctx_create; gpu::Ptx::cuda_cu_ctx_destroy_func_t gpu::Ptx::_cuda_cu_ctx_destroy; gpu::Ptx::cuda_cu_ctx_synchronize_func_t gpu::Ptx::_cuda_cu_ctx_synchronize; gpu::Ptx::cuda_cu_ctx_set_current_func_t gpu::Ptx::_cuda_cu_ctx_set_current; gpu::Ptx::cuda_cu_device_get_count_func_t gpu::Ptx::_cuda_cu_device_get_count; gpu::Ptx::cuda_cu_device_get_name_func_t gpu::Ptx::_cuda_cu_device_get_name; gpu::Ptx::cuda_cu_device_get_func_t gpu::Ptx::_cuda_cu_device_get; gpu::Ptx::cuda_cu_device_compute_capability_func_t gpu::Ptx::_cuda_cu_device_compute_capability; gpu::Ptx::cuda_cu_device_get_attribute_func_t gpu::Ptx::_cuda_cu_device_get_attribute; gpu::Ptx::cuda_cu_launch_kernel_func_t gpu::Ptx::_cuda_cu_launch_kernel; gpu::Ptx::cuda_cu_module_get_function_func_t gpu::Ptx::_cuda_cu_module_get_function; gpu::Ptx::cuda_cu_module_load_data_ex_func_t gpu::Ptx::_cuda_cu_module_load_data_ex; gpu::Ptx::cuda_cu_memcpy_dtoh_func_t gpu::Ptx::_cuda_cu_memcpy_dtoh; gpu::Ptx::cuda_cu_memfree_func_t gpu::Ptx::_cuda_cu_memfree; gpu::Ptx::cuda_cu_mem_host_register_func_t gpu::Ptx::_cuda_cu_mem_host_register; gpu::Ptx::cuda_cu_mem_host_get_device_pointer_func_t gpu::Ptx::_cuda_cu_mem_host_get_device_pointer; gpu::Ptx::cuda_cu_mem_host_unregister_func_t gpu::Ptx::_cuda_cu_mem_host_unregister; #define STRINGIFY(x) #x #define LOOKUP_CUDA_FUNCTION(name, alias) \ _##alias = \ CAST_TO_FN_PTR(alias##_func_t, os::dll_lookup(handle, STRINGIFY(name))); \ if (_##alias == NULL) { \ tty->print_cr("[CUDA] ***** Error: Failed to lookup %s", STRINGIFY(name)); \ return 0; \ } \ #define LOOKUP_CUDA_V2_FUNCTION(name, alias) LOOKUP_CUDA_FUNCTION(name##_v2, alias) /* * see http://en.wikipedia.org/wiki/CUDA#Supported_GPUs */ int ncores(int major, int minor) { int device_type = (major << 4) + minor; switch (device_type) { case 0x10: return 8; case 0x11: return 8; case 0x12: return 8; case 0x13: return 8; case 0x20: return 32; case 0x21: return 48; case 0x30: return 192; case 0x35: return 192; default: tty->print_cr("[CUDA] Warning: Unhandled device %x", device_type); return 0; } } bool gpu::Ptx::initialize_gpu() { /* Initialize CUDA driver API */ int status = _cuda_cu_init(0); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("Failed to initialize CUDA device"); return false; } if (TraceGPUInteraction) { tty->print_cr("CUDA driver initialization: Success"); } /* Get the number of compute-capable device count */ int device_count = 0; status = _cuda_cu_device_get_count(&device_count); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] Failed to get compute-capable device count"); return false; } if (device_count == 0) { tty->print_cr("[CUDA] Found no device supporting CUDA"); return false; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Number of compute-capable devices found: %d", device_count); } /* Get the handle to the first compute device */ int device_id = 0; /* Compute-capable device handle */ status = _cuda_cu_device_get(&_cu_device, device_id); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] Failed to get handle of first compute-capable device i.e., the one at ordinal: %d", device_id); return false; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Got the handle of first compute-device"); } /* Get device attributes */ int unified_addressing; status = _cuda_cu_device_get_attribute(&unified_addressing, GRAAL_CU_DEVICE_ATTRIBUTE_UNIFIED_ADDRESSING, _cu_device); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] Failed to query unified addressing mode of device: %d", _cu_device); return false; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Unified addressing support on device %d: %d", _cu_device, unified_addressing); } /* Get device name */ char device_name[256]; status = _cuda_cu_device_get_name(device_name, 256, _cu_device); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] Failed to get name of device: %d", _cu_device); return false; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Using %s", device_name); } return true; } unsigned int gpu::Ptx::total_cores() { int minor, major, nmp; int status = _cuda_cu_device_get_attribute(&minor, GRAAL_CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR, _cu_device); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] Failed to get minor attribute of device: %d", _cu_device); return 0; } status = _cuda_cu_device_get_attribute(&major, GRAAL_CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, _cu_device); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] Failed to get major attribute of device: %d", _cu_device); return 0; } status = _cuda_cu_device_get_attribute(&nmp, GRAAL_CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT, _cu_device); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] Failed to get numberof MPs on device: %d", _cu_device); return 0; } int total = nmp * ncores(major, minor); int max_threads_per_block, warp_size, async_engines, can_map_host_memory, concurrent_kernels; status = _cuda_cu_device_get_attribute(&max_threads_per_block, GRAAL_CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK, _cu_device); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] Failed to get GRAAL_CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK: %d", _cu_device); return 0; } status = _cuda_cu_device_get_attribute(&warp_size, GRAAL_CU_DEVICE_ATTRIBUTE_WARP_SIZE, _cu_device); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] Failed to get GRAAL_CU_DEVICE_ATTRIBUTE_WARP_SIZE: %d", _cu_device); return 0; } status = _cuda_cu_device_get_attribute(&async_engines, GRAAL_CU_DEVICE_ATTRIBUTE_ASYNC_ENGINE_COUNT, _cu_device); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] Failed to get GRAAL_CU_DEVICE_ATTRIBUTE_WARP_SIZE: %d", _cu_device); return 0; } status = _cuda_cu_device_get_attribute(&can_map_host_memory, GRAAL_CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY, _cu_device); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] Failed to get GRAAL_CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY: %d", _cu_device); return 0; } status = _cuda_cu_device_get_attribute(&concurrent_kernels, GRAAL_CU_DEVICE_ATTRIBUTE_CONCURRENT_KERNELS, _cu_device); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] Failed to get GRAAL_CU_DEVICE_ATTRIBUTE_CONCURRENT_KERNELS: %d", _cu_device); return 0; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Compatibility version of device %d: %d.%d", _cu_device, major, minor); tty->print_cr("[CUDA] Number of cores: %d async engines: %d can map host mem: %d concurrent kernels: %d", total, async_engines, can_map_host_memory, concurrent_kernels); tty->print_cr("[CUDA] Max threads per block: %d warp size: %d", max_threads_per_block, warp_size); } return (total); } void *gpu::Ptx::generate_kernel(unsigned char *code, int code_len, const char *name) { struct CUmod_st * cu_module; // Use three JIT compiler options const unsigned int jit_num_options = 3; int *jit_options = NEW_C_HEAP_ARRAY(int, jit_num_options, mtCompiler); void **jit_option_values = NEW_C_HEAP_ARRAY(void *, jit_num_options, mtCompiler); // Set up PTX JIT compiler options // 1. set size of compilation log buffer int jit_log_buffer_size = 1024; jit_options[0] = GRAAL_CU_JIT_INFO_LOG_BUFFER_SIZE_BYTES; jit_option_values[0] = (void *)(size_t)jit_log_buffer_size; // 2. set pointer to compilation log buffer char *jit_log_buffer = NEW_C_HEAP_ARRAY(char, jit_log_buffer_size, mtCompiler); jit_options[1] = GRAAL_CU_JIT_INFO_LOG_BUFFER; jit_option_values[1] = jit_log_buffer; // 3. set pointer to set the Maximum # of registers (32) for the kernel int jit_register_count = 32; jit_options[2] = GRAAL_CU_JIT_MAX_REGISTERS; jit_option_values[2] = (void *)(size_t)jit_register_count; /* Create CUDA context to compile and execute the kernel */ int status = _cuda_cu_ctx_create(&_device_context, GRAAL_CU_CTX_MAP_HOST, _cu_device); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] Failed to create CUDA context for device(%d): %d", _cu_device, status); return NULL; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Success: Created context for device: %d", _cu_device); } status = _cuda_cu_ctx_set_current(_device_context); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] Failed to set current context for device: %d", _cu_device); return NULL; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Success: Set current context for device: %d", _cu_device); } if (TraceGPUInteraction) { tty->print_cr("[CUDA] PTX Kernel\n%s", code); tty->print_cr("[CUDA] Function name : %s", name); } /* Load module's data with compiler options */ status = _cuda_cu_module_load_data_ex(&cu_module, (void*) code, jit_num_options, jit_options, (void **)jit_option_values); if (status != GRAAL_CUDA_SUCCESS) { if (status == GRAAL_CUDA_ERROR_NO_BINARY_FOR_GPU) { tty->print_cr("[CUDA] Check for malformed PTX kernel or incorrect PTX compilation options"); } tty->print_cr("[CUDA] *** Error (%d) Failed to load module data with online compiler options for method %s", status, name); return NULL; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Loaded data for PTX Kernel"); } struct CUfunc_st * cu_function; status = _cuda_cu_module_get_function(&cu_function, cu_module, name); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] *** Error: Failed to get function %s", name); return NULL; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Got function handle for %s", name); } return cu_function; } bool gpu::Ptx::execute_kernel(address kernel, PTXKernelArguments &ptxka, JavaValue &ret) { return gpu::Ptx::execute_warp(1, 1, 1, kernel, ptxka, ret); } bool gpu::Ptx::execute_warp(int dimX, int dimY, int dimZ, address kernel, PTXKernelArguments &ptxka, JavaValue &ret) { // grid dimensionality unsigned int gridX = 1; unsigned int gridY = 1; unsigned int gridZ = 1; // thread dimensionality unsigned int blockX = dimX; unsigned int blockY = dimY; unsigned int blockZ = dimZ; struct CUfunc_st* cu_function = (struct CUfunc_st*) kernel; void * config[5] = { GRAAL_CU_LAUNCH_PARAM_BUFFER_POINTER, ptxka._kernelArgBuffer, GRAAL_CU_LAUNCH_PARAM_BUFFER_SIZE, &(ptxka._bufferOffset), GRAAL_CU_LAUNCH_PARAM_END }; if (kernel == NULL) { return false; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] launching kernel"); } int status = _cuda_cu_launch_kernel(cu_function, gridX, gridY, gridZ, blockX, blockY, blockZ, 0, NULL, NULL, (void **) &config); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] Failed to launch kernel"); return false; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Success: Kernel Launch: X: %d Y: %d Z: %d", blockX, blockY, blockZ); } status = _cuda_cu_ctx_synchronize(); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] Failed to synchronize launched kernel (%d)", status); return false; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Success: Synchronized launch kernel"); } // Get the result. TODO: Move this code to get_return_oop() BasicType return_type = ptxka.get_ret_type(); switch (return_type) { case T_INT: { int return_val; status = gpu::Ptx::_cuda_cu_memcpy_dtoh(&return_val, ptxka._dev_return_value, T_INT_BYTE_SIZE); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] *** Error (%d) Failed to copy value to device argument", status); return false; } ret.set_jint(return_val); } break; case T_BOOLEAN: { int return_val; status = gpu::Ptx::_cuda_cu_memcpy_dtoh(&return_val, ptxka._dev_return_value, T_INT_BYTE_SIZE); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] *** Error (%d) Failed to copy value to device argument", status); return false; } ret.set_jint(return_val); } break; case T_FLOAT: { float return_val; status = gpu::Ptx::_cuda_cu_memcpy_dtoh(&return_val, ptxka._dev_return_value, T_FLOAT_BYTE_SIZE); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] *** Error (%d) Failed to copy value to device argument", status); return false; } ret.set_jfloat(return_val); } break; case T_DOUBLE: { double return_val; status = gpu::Ptx::_cuda_cu_memcpy_dtoh(&return_val, ptxka._dev_return_value, T_DOUBLE_BYTE_SIZE); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] *** Error (%d) Failed to copy value to device argument", status); return false; } ret.set_jdouble(return_val); } break; case T_LONG: { long return_val; status = gpu::Ptx::_cuda_cu_memcpy_dtoh(&return_val, ptxka._dev_return_value, T_LONG_BYTE_SIZE); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] *** Error (%d) Failed to copy value to device argument", status); return false; } ret.set_jlong(return_val); } break; case T_VOID: break; default: tty->print_cr("[CUDA] TODO *** Unhandled return type: %d", return_type); } // Free device memory allocated for result status = gpu::Ptx::_cuda_cu_memfree(ptxka._dev_return_value); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] *** Error (%d) Failed to free device memory of return value", status); return false; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Success: Freed device memory of return value"); } // Destroy context status = gpu::Ptx::_cuda_cu_ctx_destroy(_device_context); if (status != GRAAL_CUDA_SUCCESS) { tty->print_cr("[CUDA] *** Error (%d) Failed to destroy context", status); return false; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Success: Destroy context"); } return (status == GRAAL_CUDA_SUCCESS); } #if defined(LINUX) static const char cuda_library_name[] = "libcuda.so"; #elif defined(__APPLE__) static char const cuda_library_name[] = "/usr/local/cuda/lib/libcuda.dylib"; #else static char const cuda_library_name[] = ""; #endif #define STD_BUFFER_SIZE 1024 bool gpu::Ptx::probe_linkage() { if (cuda_library_name != NULL) { char *buffer = (char*)malloc(STD_BUFFER_SIZE); void *handle = os::dll_load(cuda_library_name, buffer, STD_BUFFER_SIZE); free(buffer); if (handle != NULL) { LOOKUP_CUDA_FUNCTION(cuInit, cuda_cu_init); LOOKUP_CUDA_FUNCTION(cuCtxSynchronize, cuda_cu_ctx_synchronize); LOOKUP_CUDA_FUNCTION(cuCtxSetCurrent, cuda_cu_ctx_set_current); LOOKUP_CUDA_FUNCTION(cuDeviceGetCount, cuda_cu_device_get_count); LOOKUP_CUDA_FUNCTION(cuDeviceGetName, cuda_cu_device_get_name); LOOKUP_CUDA_FUNCTION(cuDeviceGet, cuda_cu_device_get); LOOKUP_CUDA_FUNCTION(cuDeviceComputeCapability, cuda_cu_device_compute_capability); LOOKUP_CUDA_FUNCTION(cuDeviceGetAttribute, cuda_cu_device_get_attribute); LOOKUP_CUDA_FUNCTION(cuModuleGetFunction, cuda_cu_module_get_function); LOOKUP_CUDA_FUNCTION(cuModuleLoadDataEx, cuda_cu_module_load_data_ex); LOOKUP_CUDA_FUNCTION(cuLaunchKernel, cuda_cu_launch_kernel); LOOKUP_CUDA_FUNCTION(cuMemHostRegister, cuda_cu_mem_host_register); LOOKUP_CUDA_FUNCTION(cuMemHostUnregister, cuda_cu_mem_host_unregister); #if defined(__x86_64) || defined(AMD64) || defined(_M_AMD64) LOOKUP_CUDA_V2_FUNCTION(cuCtxCreate, cuda_cu_ctx_create); LOOKUP_CUDA_V2_FUNCTION(cuCtxDestroy, cuda_cu_ctx_destroy); LOOKUP_CUDA_V2_FUNCTION(cuMemAlloc, cuda_cu_memalloc); LOOKUP_CUDA_V2_FUNCTION(cuMemFree, cuda_cu_memfree); LOOKUP_CUDA_V2_FUNCTION(cuMemcpyHtoD, cuda_cu_memcpy_htod); LOOKUP_CUDA_V2_FUNCTION(cuMemcpyDtoH, cuda_cu_memcpy_dtoh); LOOKUP_CUDA_V2_FUNCTION(cuMemHostGetDevicePointer, cuda_cu_mem_host_get_device_pointer); #else LOOKUP_CUDA_FUNCTION(cuCtxCreate, cuda_cu_ctx_create); LOOKUP_CUDA_FUNCTION(cuCtxDestroy, cuda_cu_ctx_destroy); LOOKUP_CUDA_FUNCTION(cuMemAlloc, cuda_cu_memalloc); LOOKUP_CUDA_FUNCTION(cuMemFree, cuda_cu_memfree); LOOKUP_CUDA_FUNCTION(cuMemcpyHtoD, cuda_cu_memcpy_htod); LOOKUP_CUDA_FUNCTION(cuMemcpyDtoH, cuda_cu_memcpy_dtoh); LOOKUP_CUDA_FUNCTION(cuMemHostGetDevicePointer, cuda_cu_mem_host_get_device_pointer); #endif if (TraceGPUInteraction) { tty->print_cr("[CUDA] Success: library linkage"); } return true; } else { // Unable to dlopen libcuda return false; } } else { tty->print_cr("Unsupported CUDA platform"); return false; } tty->print_cr("Failed to find CUDA linkage"); return false; }