Mercurial > hg > truffle
view src/gpu/ptx/vm/gpu_ptx.cpp @ 16522:8bba3477c88c
[SPARC] Implementing visitInfopointNode
author | Stefan Anzinger <stefan.anzinger@gmail.com> |
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date | Mon, 14 Jul 2014 05:04:45 -0700 |
parents | 063ec2920d21 |
children | f55f2d400797 |
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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 "ptx/vm/gpu_ptx.hpp" #include "utilities/globalDefinitions.hpp" #include "utilities/ostream.hpp" #include "memory/allocation.hpp" #include "memory/allocation.inline.hpp" #include "memory/gcLocker.inline.hpp" #include "runtime/interfaceSupport.hpp" #include "runtime/vframe.hpp" #include "graal/graalEnv.hpp" #include "graal/graalRuntime.hpp" #define T_BYTE_SIZE 1 #define T_BOOLEAN_SIZE 4 #define T_INT_BYTE_SIZE 4 #define T_FLOAT_BYTE_SIZE 4 #define T_DOUBLE_BYTE_SIZE 8 #define T_LONG_BYTE_SIZE 8 #define T_OBJECT_BYTE_SIZE sizeof(intptr_t) #define T_ARRAY_BYTE_SIZE sizeof(intptr_t) // Entry to GPU native method implementation that transitions current thread to '_thread_in_vm'. #define GPU_VMENTRY(result_type, name, signature) \ JNIEXPORT result_type JNICALL name signature { \ if (TraceGPUInteraction) tty->print_cr("[CUDA] " #name); \ GRAAL_VM_ENTRY_MARK; \ // Entry to GPU native method implementation that calls a JNI function // and hence cannot transition current thread to '_thread_in_vm'. #define GPU_ENTRY(result_type, name, signature) \ JNIEXPORT result_type JNICALL name signature { \ if (TraceGPUInteraction) tty->print_cr("[CUDA] Ptx::" #name); \ #define GPU_END } #define CC (char*) /*cast a literal from (const char*)*/ #define FN_PTR(f) CAST_FROM_FN_PTR(void*, &(f)) #define STRING "Ljava/lang/String;" JNINativeMethod Ptx::PTX_methods[] = { {CC"initialize", CC"()Z", FN_PTR(Ptx::initialize)}, {CC"generateKernel", CC"([B" STRING ")J", FN_PTR(Ptx::generate_kernel)}, {CC"getLaunchKernelAddress", CC"()J", FN_PTR(Ptx::get_execute_kernel_from_vm_address)}, {CC"getAvailableProcessors0", CC"()I", FN_PTR(Ptx::get_total_cores)}, {CC"destroyContext", CC"()V", FN_PTR(Ptx::destroy_ptx_context)}, }; void * Ptx::_device_context = 0; int Ptx::_cu_device = 0; Ptx::cuda_cu_init_func_t Ptx::_cuda_cu_init; Ptx::cuda_cu_ctx_create_func_t Ptx::_cuda_cu_ctx_create; Ptx::cuda_cu_ctx_destroy_func_t Ptx::_cuda_cu_ctx_destroy; Ptx::cuda_cu_ctx_synchronize_func_t Ptx::_cuda_cu_ctx_synchronize; Ptx::cuda_cu_ctx_get_current_func_t Ptx::_cuda_cu_ctx_get_current; Ptx::cuda_cu_ctx_set_current_func_t Ptx::_cuda_cu_ctx_set_current; Ptx::cuda_cu_device_get_count_func_t Ptx::_cuda_cu_device_get_count; Ptx::cuda_cu_device_get_name_func_t Ptx::_cuda_cu_device_get_name; Ptx::cuda_cu_device_get_func_t Ptx::_cuda_cu_device_get; Ptx::cuda_cu_device_compute_capability_func_t Ptx::_cuda_cu_device_compute_capability; Ptx::cuda_cu_device_get_attribute_func_t Ptx::_cuda_cu_device_get_attribute; Ptx::cuda_cu_launch_kernel_func_t Ptx::_cuda_cu_launch_kernel; Ptx::cuda_cu_module_get_function_func_t Ptx::_cuda_cu_module_get_function; Ptx::cuda_cu_module_load_data_ex_func_t Ptx::_cuda_cu_module_load_data_ex; Ptx::cuda_cu_memcpy_htod_func_t Ptx::_cuda_cu_memcpy_htod; Ptx::cuda_cu_memcpy_dtoh_func_t Ptx::_cuda_cu_memcpy_dtoh; Ptx::cuda_cu_memalloc_func_t Ptx::_cuda_cu_memalloc; Ptx::cuda_cu_memfree_func_t Ptx::_cuda_cu_memfree; Ptx::cuda_cu_mem_host_register_func_t Ptx::_cuda_cu_mem_host_register; Ptx::cuda_cu_mem_host_get_device_pointer_func_t Ptx::_cuda_cu_mem_host_get_device_pointer; Ptx::cuda_cu_mem_host_unregister_func_t 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 false; \ } \ #define LOOKUP_CUDA_V2_FUNCTION(name, alias) LOOKUP_CUDA_FUNCTION(name##_v2, alias) /* * see http://en.wikipedia.org/wiki/CUDA#Supported_GPUs */ int Ptx::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 Ptx::register_natives(JNIEnv* env) { jclass klass = env->FindClass("com/oracle/graal/hotspot/ptx/PTXHotSpotBackend"); if (klass == NULL) { if (TraceGPUInteraction) { tty->print_cr("PTXHotSpotBackend class not found"); } return false; } jint status = env->RegisterNatives(klass, PTX_methods, sizeof(PTX_methods) / sizeof(JNINativeMethod)); if (status != JNI_OK) { if (true || TraceGPUInteraction) { tty->print_cr("Error registering natives for PTXHotSpotBackend: %d", status); } return false; } return true; } GPU_ENTRY(jboolean, Ptx::initialize, (JNIEnv *env, jclass)) if (!link()) { return false; } /* Initialize CUDA driver API */ int status = _cuda_cu_init(0); if (status != GRAAL_CUDA_SUCCESS) { if (TraceGPUInteraction) { tty->print_cr("Failed to initialize CUDA device: %d", status); } 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 minor, major; int unified_addressing; float version = 0.0; /* Get the compute capability of the device found */ 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 false; } 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 false; } /* Check if the device supports atleast GRAAL_SUPPORTED_COMPUTE_CAPABILITY_VERSION */ version = (float) major + ((float) minor)/10; if (version < GRAAL_SUPPORTED_COMPUTE_CAPABILITY_VERSION) { tty->print_cr("[CUDA] Only cuda compute capability %.1f and later supported. Device %d supports %.1f", (float) GRAAL_SUPPORTED_COMPUTE_CAPABILITY_VERSION, _cu_device, version); return false; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Device %d supports cuda compute capability %.1f", _cu_device, version); } 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; } /* The CUDA driver runtime interaction and generated code as implemented requires that the device supports Unified Addressing. */ if (unified_addressing == 0) { tty->print_cr("[CUDA] CUDA device %d does NOT have required Unified Addressing support.", _cu_device); return false; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Device %d has Unified Addressing support", _cu_device); } /* 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); } // Create CUDA context to compile and execute the kernel 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 false; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Success: Created context for device: %d", _cu_device); } Gpu::initialized_gpu(new Ptx()); return true; GPU_END GPU_ENTRY(jint, Ptx::get_total_cores, (JNIEnv *env, jobject)) 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 number of 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] 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; GPU_END GPU_ENTRY(jlong, Ptx::generate_kernel, (JNIEnv *env, jclass, jbyteArray code_handle, jstring name_handle)) ResourceMark rm; jsize name_len = env->GetStringLength(name_handle); jsize code_len = env->GetArrayLength(code_handle); char* name = NEW_RESOURCE_ARRAY(char, name_len + 1); unsigned char *code = NEW_RESOURCE_ARRAY(unsigned char, code_len + 1); code[code_len] = 0; name[name_len] = 0; env->GetByteArrayRegion(code_handle, 0, code_len, (jbyte*) code); env->GetStringUTFRegion(name_handle, 0, name_len, name); struct CUmod_st * cu_module; // Use three JIT compiler options const unsigned int jit_num_options = 3; int *jit_options = NEW_RESOURCE_ARRAY(int, jit_num_options); void **jit_option_values = NEW_RESOURCE_ARRAY(void *, jit_num_options); // 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_RESOURCE_ARRAY(char, jit_log_buffer_size); jit_options[1] = GRAAL_CU_JIT_INFO_LOG_BUFFER; jit_option_values[1] = jit_log_buffer; // 3. set pointer to set the maximum number 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; // Set CUDA context to compile and execute the kernel if (_device_context == NULL) { tty->print_cr("[CUDA] Encountered uninitialized CUDA context for device(%d)", _cu_device); return 0L; } int 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 0L; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Success: Set current context for device: %d", _cu_device); 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 0L; } 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 0L; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Got function handle for %s kernel address %p", name, cu_function); } return (jlong) cu_function; GPU_END // A PtxCall is used to manage executing a GPU kernel. In addition to launching // the kernel, this class releases resources allocated for the execution. class PtxCall: StackObj { private: JavaThread* _thread; // the thread on which this call is made address _buffer; // buffer containing parameters and _return_value int _buffer_size; // size (in bytes) of _buffer oop* _pinned; // objects that have been pinned with cuMemHostRegister int _pinned_length; // length of _pinned Ptx::CUdeviceptr _ret_value; // pointer to slot in GPU memory holding the return value int _ret_type_size; // size of the return type value bool _ret_is_object; // specifies if the return type is Object bool _gc_locked; // denotes when execution has locked GC bool check(int status, const char *action) { if (status != GRAAL_CUDA_SUCCESS) { Thread* THREAD = _thread; ResourceMark rm(THREAD); char* message = NEW_RESOURCE_ARRAY_IN_THREAD(THREAD, char, O_BUFLEN + 1); jio_snprintf(message, O_BUFLEN, "[CUDA] *** Error (status=%d): %s", status, action); if (TraceGPUInteraction) { tty->print_cr(message); } if (!HAS_PENDING_EXCEPTION) { SharedRuntime::throw_and_post_jvmti_exception(_thread, vmSymbols::java_lang_RuntimeException(), message); } return false; } if (TraceGPUInteraction) { tty->print_cr("[CUDA] Success: %s", action); } return true; } public: PtxCall(JavaThread* thread, address buffer, int buffer_size, oop* pinned, int encodedReturnTypeSize) : _thread(thread), _gc_locked(false), _buffer(buffer), _buffer_size(buffer_size), _pinned(pinned), _pinned_length(0), _ret_value(0), _ret_is_object(encodedReturnTypeSize < 0) { _ret_type_size = _ret_is_object ? -encodedReturnTypeSize : encodedReturnTypeSize; } bool is_object_return() { return _ret_is_object; } void alloc_return_value() { if (_ret_type_size != 0) { if (check(Ptx::_cuda_cu_memalloc(&_ret_value, _ret_type_size), "Allocate device memory for return value")) { Ptx::CUdeviceptr* retValuePtr = (Ptx::CUdeviceptr*) ((_buffer + _buffer_size) - sizeof(_ret_value)); *retValuePtr = _ret_value; } } } void pin_objects(int count, int* objectOffsets) { if (count == 0) { return; } // Once we start pinning objects, no GC must occur // until the kernel has completed. This is a big // hammer for ensuring we can safely pass objects // to the GPU. GC_locker::lock_critical(_thread); _gc_locked = true; if (TraceGPUInteraction) { tty->print_cr("[CUDA] Locked GC"); } for (int i = 0; i < count; i++) { int offset = objectOffsets[i]; oop* argPtr = (oop*) (_buffer + offset); oop obj = *argPtr; if (obj != NULL) { // Size (in bytes) of object int objSize = obj->size() * HeapWordSize; //tty->print_cr("Pinning object %d at offset %d: %p", i, offset, obj); if (!check(Ptx::_cuda_cu_mem_host_register(obj, objSize, GRAAL_CU_MEMHOSTREGISTER_DEVICEMAP), "Pin object")) { return; } // Record original oop so that its memory can be unpinned _pinned[_pinned_length++] = obj; // Replace host pointer to object with device pointer // to object in kernel parameters buffer if (!check(Ptx::_cuda_cu_mem_host_get_device_pointer((Ptx::CUdeviceptr*) argPtr, obj, 0), "Get device pointer for pinned object")) { return; } } } } void launch(address kernel, jint dimX, jint dimY, jint dimZ) { // grid dimensionality unsigned int gridX = 1; unsigned int gridY = 1; unsigned int gridZ = 1; void * config[] = { GRAAL_CU_LAUNCH_PARAM_BUFFER_POINTER, (char*) (address) _buffer, GRAAL_CU_LAUNCH_PARAM_BUFFER_SIZE, &_buffer_size, GRAAL_CU_LAUNCH_PARAM_END }; if (check(Ptx::_cuda_cu_launch_kernel((struct CUfunc_st*) (address) kernel, gridX, gridY, gridZ, dimX, dimY, dimZ, 0, NULL, NULL, (void**) &config), "Launch kernel")) { } } void synchronize() { check(Ptx::_cuda_cu_ctx_synchronize(), "Synchronize kernel"); } void unpin_objects() { while (_pinned_length > 0) { oop obj = _pinned[--_pinned_length]; assert(obj != NULL, "npe"); //tty->print_cr("Unpinning object %d: %p", _pinned_length, obj); if (!check(Ptx::_cuda_cu_mem_host_unregister(obj), "Unpin object")) { return; } } } oop get_object_return_value() { oop return_val; check(Ptx::_cuda_cu_memcpy_dtoh(&return_val, _ret_value, T_OBJECT_BYTE_SIZE), "Copy return value from device"); return return_val; } jlong get_primitive_return_value() { jlong return_val; check(Ptx::_cuda_cu_memcpy_dtoh(&return_val, _ret_value, _ret_type_size), "Copy return value from device"); return return_val; } void free_return_value() { if (_ret_value != 0) { check(Ptx::_cuda_cu_memfree(_ret_value), "Free device memory"); _ret_value = 0; } } ~PtxCall() { unpin_objects(); free_return_value(); if (_gc_locked) { GC_locker::unlock_critical(_thread); if (TraceGPUInteraction) { tty->print_cr("[CUDA] Unlocked GC"); } _gc_locked = false; } } }; // Prints values in the kernel arguments buffer class KernelArgumentsPrinter: public SignatureIterator { Method* _method; address _buffer; size_t _bufferOffset; outputStream* _st; private: // Get next java argument oop next_arg(BasicType expectedType); public: KernelArgumentsPrinter(Method* method, address buffer, outputStream* st) : SignatureIterator(method->signature()), _method(method), _buffer(buffer), _bufferOffset(0), _st(st) { if (!method->is_static()) { print_oop(); } iterate(); } address next(size_t dataSz) { if (is_return_type()) { return _buffer; } if (_bufferOffset != 0) { _st->print(", "); } _bufferOffset = align_size_up_(_bufferOffset, dataSz); address result = _buffer + _bufferOffset; _bufferOffset += dataSz; return result; } void print_oop() { oop obj = *((oop*) next(sizeof(oop))); if (obj != NULL) { char type[256]; obj->klass()->name()->as_C_string(type, 256); _st->print("oop "PTR_FORMAT" (%s)", (address) obj, type); } else { _st->print("oop null"); } } bool skip() { return is_return_type(); } void do_bool () { if (!skip()) _st->print("bool %d", *((jboolean*) next(sizeof(jboolean)))); } void do_char () { if (!skip()) _st->print("char %c", *((jchar*) next(sizeof(jchar)))); } void do_float () { if (!skip()) _st->print("float %g", *((jfloat*) next(sizeof(jfloat)))); } void do_double() { if (!skip()) _st->print("double %g", *((jdouble*) next(sizeof(jdouble)))); } void do_byte () { if (!skip()) _st->print("byte %d", *((jbyte*) next(sizeof(jbyte)))); } void do_short () { if (!skip()) _st->print("short %d", *((jshort*) next(sizeof(jshort)))); } void do_int () { if (!skip()) _st->print("int %d", *((jint*) next(sizeof(jint)))); } void do_long () { if (!skip()) _st->print("long "JLONG_FORMAT, *((jlong*) next(sizeof(jlong)))); } void do_void () { } void do_object(int begin, int end) { if (!skip()) print_oop(); } void do_array (int begin, int end) { if (!skip()) print_oop(); } }; static void printKernelArguments(JavaThread* thread, address buffer) { for (vframeStream vfst(thread); !vfst.at_end(); vfst.next()) { Method* m = vfst.method(); if (m != NULL) { ResourceMark rm; stringStream st(O_BUFLEN); st.print("[CUDA] Call: %s.%s(", m->method_holder()->name()->as_C_string(), m->name()->as_C_string()); KernelArgumentsPrinter kap(m, buffer, &st); tty->print_cr("%s)", st.as_string()); return; } } } GPU_VMENTRY(void, Ptx::destroy_ptx_context, (void)) if (_device_context != NULL) { int status = _cuda_cu_ctx_destroy(_device_context); if (status != GRAAL_CUDA_SUCCESS) { if (TraceGPUInteraction) { tty->print_cr("[CUDA] Error(%d) : Failed to destroy context", status); } _device_context = NULL; } else { if (TraceGPUInteraction) { tty->print_cr("[CUDA] Destroyed context", status); } } } GPU_END GPU_VMENTRY(jlong, Ptx::get_execute_kernel_from_vm_address, (JNIEnv *env, jclass)) return (jlong) Ptx::execute_kernel_from_vm; GPU_END JRT_ENTRY(jlong, Ptx::execute_kernel_from_vm(JavaThread* thread, jlong kernel, jint dimX, jint dimY, jint dimZ, jlong buffer, jint bufferSize, jint objectParametersCount, jlong objectParametersOffsets, jlong pinnedObjects, int encodedReturnTypeSize)) if (kernel == 0L) { SharedRuntime::throw_and_post_jvmti_exception(thread, vmSymbols::java_lang_NullPointerException(), NULL); return 0L; } if (TraceGPUInteraction) { printKernelArguments(thread, (address) buffer); } PtxCall call(thread, (address) buffer, bufferSize, (oop*) (address) pinnedObjects, encodedReturnTypeSize); #define TRY(action) do { \ action; \ if (HAS_PENDING_EXCEPTION) return 0L; \ } while (0) TRY(call.alloc_return_value()); TRY(call.pin_objects(objectParametersCount, (int*) (address) objectParametersOffsets)); TRY(call.launch((address) kernel, dimX, dimY, dimZ)); TRY(call.synchronize()); if (call.is_object_return()) { oop return_val; TRY(return_val = call.get_object_return_value()); thread->set_vm_result(return_val); return 0L; } jlong return_val; TRY(return_val = call.get_primitive_return_value()); return return_val; #undef TRY JRT_END #if defined(LINUX) static const char cuda_library_name[] = "/usr/lib/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 bool Ptx::link() { if (cuda_library_name == NULL) { if (TraceGPUInteraction) { tty->print_cr("Failed to find CUDA linkage"); } return false; } char ebuf[O_BUFLEN]; void *handle = os::dll_load(cuda_library_name, ebuf, O_BUFLEN); if (handle == NULL) { if (TraceGPUInteraction) { tty->print_cr("Unsupported CUDA platform: %s", ebuf); } return false; } LOOKUP_CUDA_FUNCTION(cuInit, cuda_cu_init); LOOKUP_CUDA_FUNCTION(cuCtxSynchronize, cuda_cu_ctx_synchronize); LOOKUP_CUDA_FUNCTION(cuCtxGetCurrent, cuda_cu_ctx_get_current); 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; }