Mercurial > hg > graal-jvmci-8
annotate src/gpu/ptx/vm/gpu_ptx.cpp @ 13819:49db2c1e3bee
added support for co-existing GPU backends (JBS:GRAAL-1)
author | Doug Simon <doug.simon@oracle.com> |
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date | Thu, 30 Jan 2014 00:52:33 +0100 |
parents | 80cd5c3b8827 |
children | 5c8a3c09397b ab370d74a8eb |
rev | line source |
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10879 | 1 /* |
2 * Copyright (c) 2013, Oracle and/or its affiliates. All rights reserved. | |
3 * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. | |
4 * | |
5 * This code is free software; you can redistribute it and/or modify it | |
6 * under the terms of the GNU General Public License version 2 only, as | |
7 * published by the Free Software Foundation. | |
8 * | |
9 * This code is distributed in the hope that it will be useful, but WITHOUT | |
10 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or | |
11 * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License | |
12 * version 2 for more details (a copy is included in the LICENSE file that | |
13 * accompanied this code). | |
14 * | |
15 * You should have received a copy of the GNU General Public License version | |
16 * 2 along with this work; if not, write to the Free Software Foundation, | |
17 * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. | |
18 * | |
19 * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA | |
20 * or visit www.oracle.com if you need additional information or have any | |
21 * questions. | |
22 * | |
23 */ | |
24 | |
25 #include "precompiled.hpp" | |
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26 #include "runtime/javaCalls.hpp" |
10879 | 27 #include "runtime/gpu.hpp" |
28 #include "utilities/globalDefinitions.hpp" | |
29 #include "utilities/ostream.hpp" | |
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30 #include "memory/allocation.hpp" |
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31 #include "memory/allocation.inline.hpp" |
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32 #include "runtime/interfaceSupport.hpp" |
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33 #include "graal/graalEnv.hpp" |
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34 #include "graal/graalCompiler.hpp" |
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35 #include "ptxKernelArguments.hpp" |
10879 | 36 |
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37 // Entry to GPU native method implementation that transitions current thread to '_thread_in_vm'. |
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38 #define GPU_VMENTRY(result_type, name, signature) \ |
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39 JNIEXPORT result_type JNICALL name signature { \ |
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40 GRAAL_VM_ENTRY_MARK; \ |
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41 |
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42 // Entry to GPU native method implementation that calls a JNI function |
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43 // and hence cannot transition current thread to '_thread_in_vm'. |
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44 #define GPU_ENTRY(result_type, name, signature) \ |
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45 JNIEXPORT result_type JNICALL name signature { \ |
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46 |
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47 #define GPU_END } |
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48 |
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49 #define CC (char*) /*cast a literal from (const char*)*/ |
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50 #define FN_PTR(f) CAST_FROM_FN_PTR(void*, &(f)) |
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51 |
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52 #define STRING "Ljava/lang/String;" |
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53 |
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54 JNINativeMethod gpu::Ptx::PTX_methods[] = { |
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55 {CC"initialize", CC"()Z", FN_PTR(gpu::Ptx::initialize)}, |
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56 {CC"generateKernel", CC"([B" STRING ")J", FN_PTR(gpu::Ptx::generate_kernel)}, |
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57 {CC"getLaunchKernelAddress", CC"()J", FN_PTR(gpu::Ptx::get_execute_kernel_from_vm_address)}, |
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58 {CC"getAvailableProcessors0", CC"()I", FN_PTR(gpu::Ptx::get_total_cores)}, |
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59 }; |
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60 |
10879 | 61 void * gpu::Ptx::_device_context; |
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62 int gpu::Ptx::_cu_device = 0; |
10879 | 63 |
64 gpu::Ptx::cuda_cu_init_func_t gpu::Ptx::_cuda_cu_init; | |
65 gpu::Ptx::cuda_cu_ctx_create_func_t gpu::Ptx::_cuda_cu_ctx_create; | |
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66 gpu::Ptx::cuda_cu_ctx_destroy_func_t gpu::Ptx::_cuda_cu_ctx_destroy; |
10879 | 67 gpu::Ptx::cuda_cu_ctx_synchronize_func_t gpu::Ptx::_cuda_cu_ctx_synchronize; |
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68 gpu::Ptx::cuda_cu_ctx_get_current_func_t gpu::Ptx::_cuda_cu_ctx_get_current; |
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69 gpu::Ptx::cuda_cu_ctx_set_current_func_t gpu::Ptx::_cuda_cu_ctx_set_current; |
10879 | 70 gpu::Ptx::cuda_cu_device_get_count_func_t gpu::Ptx::_cuda_cu_device_get_count; |
71 gpu::Ptx::cuda_cu_device_get_name_func_t gpu::Ptx::_cuda_cu_device_get_name; | |
72 gpu::Ptx::cuda_cu_device_get_func_t gpu::Ptx::_cuda_cu_device_get; | |
73 gpu::Ptx::cuda_cu_device_compute_capability_func_t gpu::Ptx::_cuda_cu_device_compute_capability; | |
74 gpu::Ptx::cuda_cu_device_get_attribute_func_t gpu::Ptx::_cuda_cu_device_get_attribute; | |
75 gpu::Ptx::cuda_cu_launch_kernel_func_t gpu::Ptx::_cuda_cu_launch_kernel; | |
76 gpu::Ptx::cuda_cu_module_get_function_func_t gpu::Ptx::_cuda_cu_module_get_function; | |
77 gpu::Ptx::cuda_cu_module_load_data_ex_func_t gpu::Ptx::_cuda_cu_module_load_data_ex; | |
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78 gpu::Ptx::cuda_cu_memcpy_dtoh_func_t gpu::Ptx::_cuda_cu_memcpy_dtoh; |
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79 gpu::Ptx::cuda_cu_memfree_func_t gpu::Ptx::_cuda_cu_memfree; |
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80 gpu::Ptx::cuda_cu_mem_host_register_func_t gpu::Ptx::_cuda_cu_mem_host_register; |
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81 gpu::Ptx::cuda_cu_mem_host_get_device_pointer_func_t gpu::Ptx::_cuda_cu_mem_host_get_device_pointer; |
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82 gpu::Ptx::cuda_cu_mem_host_unregister_func_t gpu::Ptx::_cuda_cu_mem_host_unregister; |
10879 | 83 |
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84 #define STRINGIFY(x) #x |
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85 |
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86 #define LOOKUP_CUDA_FUNCTION(name, alias) \ |
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87 _##alias = \ |
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88 CAST_TO_FN_PTR(alias##_func_t, os::dll_lookup(handle, STRINGIFY(name))); \ |
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89 if (_##alias == NULL) { \ |
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90 tty->print_cr("[CUDA] ***** Error: Failed to lookup %s", STRINGIFY(name)); \ |
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91 return false; \ |
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92 } \ |
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93 |
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94 #define LOOKUP_CUDA_V2_FUNCTION(name, alias) LOOKUP_CUDA_FUNCTION(name##_v2, alias) |
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95 |
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96 /* |
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97 * see http://en.wikipedia.org/wiki/CUDA#Supported_GPUs |
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98 */ |
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99 int gpu::Ptx::ncores(int major, int minor) { |
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100 int device_type = (major << 4) + minor; |
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101 |
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102 switch (device_type) { |
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103 case 0x10: return 8; |
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104 case 0x11: return 8; |
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105 case 0x12: return 8; |
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106 case 0x13: return 8; |
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107 case 0x20: return 32; |
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108 case 0x21: return 48; |
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109 case 0x30: return 192; |
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110 case 0x35: return 192; |
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111 default: |
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112 tty->print_cr("[CUDA] Warning: Unhandled device %x", device_type); |
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113 return 0; |
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114 } |
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115 } |
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116 |
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117 bool gpu::Ptx::register_natives(JNIEnv* env) { |
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118 jclass klass = env->FindClass("com/oracle/graal/hotspot/ptx/PTXHotSpotBackend"); |
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119 if (klass == NULL) { |
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120 if (TraceGPUInteraction) { |
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121 tty->print_cr("PTXHotSpotBackend class not found"); |
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122 } |
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123 return false; |
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124 } |
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125 jint status = env->RegisterNatives(klass, PTX_methods, sizeof(PTX_methods) / sizeof(JNINativeMethod)); |
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126 if (status != JNI_OK) { |
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127 if (TraceGPUInteraction) { |
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128 tty->print_cr("Error registering natives for PTXHotSpotBackend: %d", status); |
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129 } |
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130 return false; |
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131 } |
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132 return true; |
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133 } |
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134 |
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135 GPU_ENTRY(jboolean, gpu::Ptx::initialize, (JNIEnv *env, jclass)) |
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136 |
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137 if (!link()) { |
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138 return false; |
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139 } |
10879 | 140 |
141 /* Initialize CUDA driver API */ | |
142 int status = _cuda_cu_init(0); | |
143 if (status != GRAAL_CUDA_SUCCESS) { | |
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144 if (TraceGPUInteraction) { |
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145 tty->print_cr("Failed to initialize CUDA device: %d", status); |
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146 } |
10879 | 147 return false; |
148 } | |
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149 |
10879 | 150 if (TraceGPUInteraction) { |
151 tty->print_cr("CUDA driver initialization: Success"); | |
152 } | |
153 | |
154 /* Get the number of compute-capable device count */ | |
155 int device_count = 0; | |
156 status = _cuda_cu_device_get_count(&device_count); | |
157 if (status != GRAAL_CUDA_SUCCESS) { | |
158 tty->print_cr("[CUDA] Failed to get compute-capable device count"); | |
159 return false; | |
160 } | |
161 | |
162 if (device_count == 0) { | |
163 tty->print_cr("[CUDA] Found no device supporting CUDA"); | |
164 return false; | |
165 } | |
166 | |
167 if (TraceGPUInteraction) { | |
168 tty->print_cr("[CUDA] Number of compute-capable devices found: %d", device_count); | |
169 } | |
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170 |
10879 | 171 /* Get the handle to the first compute device */ |
172 int device_id = 0; | |
173 /* Compute-capable device handle */ | |
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174 status = _cuda_cu_device_get(&_cu_device, device_id); |
10879 | 175 |
176 if (status != GRAAL_CUDA_SUCCESS) { | |
177 tty->print_cr("[CUDA] Failed to get handle of first compute-capable device i.e., the one at ordinal: %d", device_id); | |
178 return false; | |
179 } | |
180 | |
181 if (TraceGPUInteraction) { | |
182 tty->print_cr("[CUDA] Got the handle of first compute-device"); | |
183 } | |
184 | |
185 /* Get device attributes */ | |
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186 int unified_addressing; |
10879 | 187 |
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188 status = _cuda_cu_device_get_attribute(&unified_addressing, GRAAL_CU_DEVICE_ATTRIBUTE_UNIFIED_ADDRESSING, _cu_device); |
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189 |
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190 if (status != GRAAL_CUDA_SUCCESS) { |
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191 tty->print_cr("[CUDA] Failed to query unified addressing mode of device: %d", _cu_device); |
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192 return false; |
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193 } |
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194 |
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195 if (TraceGPUInteraction) { |
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196 tty->print_cr("[CUDA] Unified addressing support on device %d: %d", _cu_device, unified_addressing); |
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197 } |
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198 |
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199 |
10879 | 200 /* Get device name */ |
201 char device_name[256]; | |
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202 status = _cuda_cu_device_get_name(device_name, 256, _cu_device); |
10879 | 203 |
204 if (status != GRAAL_CUDA_SUCCESS) { | |
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205 tty->print_cr("[CUDA] Failed to get name of device: %d", _cu_device); |
10879 | 206 return false; |
207 } | |
208 | |
209 if (TraceGPUInteraction) { | |
210 tty->print_cr("[CUDA] Using %s", device_name); | |
211 } | |
212 | |
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213 gpu::initialized_gpu(device_name); |
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214 |
10879 | 215 return true; |
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216 GPU_END |
10879 | 217 |
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218 GPU_ENTRY(jint, gpu::Ptx::get_total_cores, (JNIEnv *env, jobject)) |
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219 |
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220 int minor, major, nmp; |
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221 int status = _cuda_cu_device_get_attribute(&minor, |
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222 GRAAL_CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR, |
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223 _cu_device); |
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224 |
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225 if (status != GRAAL_CUDA_SUCCESS) { |
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226 tty->print_cr("[CUDA] Failed to get minor attribute of device: %d", _cu_device); |
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227 return 0; |
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228 } |
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229 |
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230 status = _cuda_cu_device_get_attribute(&major, |
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231 GRAAL_CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, |
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232 _cu_device); |
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233 |
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234 if (status != GRAAL_CUDA_SUCCESS) { |
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235 tty->print_cr("[CUDA] Failed to get major attribute of device: %d", _cu_device); |
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236 return 0; |
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237 } |
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238 |
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239 status = _cuda_cu_device_get_attribute(&nmp, |
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240 GRAAL_CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT, |
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241 _cu_device); |
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242 |
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243 if (status != GRAAL_CUDA_SUCCESS) { |
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244 tty->print_cr("[CUDA] Failed to get number of MPs on device: %d", _cu_device); |
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245 return 0; |
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246 } |
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247 |
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248 int total = nmp * ncores(major, minor); |
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249 |
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250 int max_threads_per_block, warp_size, async_engines, can_map_host_memory, concurrent_kernels; |
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251 |
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252 status = _cuda_cu_device_get_attribute(&max_threads_per_block, |
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253 GRAAL_CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK, |
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254 _cu_device); |
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255 |
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256 if (status != GRAAL_CUDA_SUCCESS) { |
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257 tty->print_cr("[CUDA] Failed to get GRAAL_CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK: %d", _cu_device); |
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258 return 0; |
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259 } |
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260 |
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261 status = _cuda_cu_device_get_attribute(&warp_size, |
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262 GRAAL_CU_DEVICE_ATTRIBUTE_WARP_SIZE, |
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263 _cu_device); |
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264 |
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265 if (status != GRAAL_CUDA_SUCCESS) { |
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266 tty->print_cr("[CUDA] Failed to get GRAAL_CU_DEVICE_ATTRIBUTE_WARP_SIZE: %d", _cu_device); |
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267 return 0; |
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268 } |
12653
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* PTX kernel argument buffer now has naturally aligned arguments as required by PTX JIT compiler.
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269 |
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270 status = _cuda_cu_device_get_attribute(&async_engines, |
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271 GRAAL_CU_DEVICE_ATTRIBUTE_ASYNC_ENGINE_COUNT, |
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272 _cu_device); |
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273 |
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274 if (status != GRAAL_CUDA_SUCCESS) { |
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275 tty->print_cr("[CUDA] Failed to get GRAAL_CU_DEVICE_ATTRIBUTE_WARP_SIZE: %d", _cu_device); |
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276 return 0; |
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277 } |
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278 |
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279 status = _cuda_cu_device_get_attribute(&can_map_host_memory, |
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280 GRAAL_CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY, |
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281 _cu_device); |
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282 |
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283 if (status != GRAAL_CUDA_SUCCESS) { |
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284 tty->print_cr("[CUDA] Failed to get GRAAL_CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY: %d", _cu_device); |
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285 return 0; |
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Fixed BasicPTXTest and IntegerPTXTest
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286 } |
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287 |
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288 status = _cuda_cu_device_get_attribute(&concurrent_kernels, |
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289 GRAAL_CU_DEVICE_ATTRIBUTE_CONCURRENT_KERNELS, |
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290 _cu_device); |
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291 |
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292 if (status != GRAAL_CUDA_SUCCESS) { |
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293 tty->print_cr("[CUDA] Failed to get GRAAL_CU_DEVICE_ATTRIBUTE_CONCURRENT_KERNELS: %d", _cu_device); |
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294 return 0; |
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295 } |
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296 |
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297 if (TraceGPUInteraction) { |
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298 tty->print_cr("[CUDA] Compatibility version of device %d: %d.%d", _cu_device, major, minor); |
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299 tty->print_cr("[CUDA] Number of cores: %d async engines: %d can map host mem: %d concurrent kernels: %d", |
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300 total, async_engines, can_map_host_memory, concurrent_kernels); |
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301 tty->print_cr("[CUDA] Max threads per block: %d warp size: %d", max_threads_per_block, warp_size); |
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302 } |
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303 return total; |
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304 GPU_END |
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305 |
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306 GPU_ENTRY(jlong, gpu::Ptx::generate_kernel, (JNIEnv *env, jclass, jbyteArray code_handle, jstring name_handle)) |
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307 ResourceMark rm; |
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308 jsize name_len = env->GetStringLength(name_handle); |
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309 jsize code_len = env->GetArrayLength(code_handle); |
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310 |
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311 char* name = NEW_RESOURCE_ARRAY(char, name_len + 1); |
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312 unsigned char *code = NEW_RESOURCE_ARRAY(unsigned char, code_len + 1); |
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313 |
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314 code[code_len] = 0; |
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315 name[name_len] = 0; |
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316 |
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317 env->GetByteArrayRegion(code_handle, 0, code_len, (jbyte*) code); |
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318 env->GetStringUTFRegion(name_handle, 0, name_len, name); |
10879 | 319 |
320 struct CUmod_st * cu_module; | |
321 // Use three JIT compiler options | |
322 const unsigned int jit_num_options = 3; | |
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323 int *jit_options = NEW_RESOURCE_ARRAY(int, jit_num_options); |
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324 void **jit_option_values = NEW_RESOURCE_ARRAY(void *, jit_num_options); |
10879 | 325 |
326 // Set up PTX JIT compiler options | |
327 // 1. set size of compilation log buffer | |
328 int jit_log_buffer_size = 1024; | |
329 jit_options[0] = GRAAL_CU_JIT_INFO_LOG_BUFFER_SIZE_BYTES; | |
330 jit_option_values[0] = (void *)(size_t)jit_log_buffer_size; | |
331 | |
332 // 2. set pointer to compilation log buffer | |
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333 char *jit_log_buffer = NEW_RESOURCE_ARRAY(char, jit_log_buffer_size); |
10879 | 334 jit_options[1] = GRAAL_CU_JIT_INFO_LOG_BUFFER; |
335 jit_option_values[1] = jit_log_buffer; | |
336 | |
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337 // 3. set pointer to set the maximum number of registers (32) for the kernel |
10879 | 338 int jit_register_count = 32; |
339 jit_options[2] = GRAAL_CU_JIT_MAX_REGISTERS; | |
340 jit_option_values[2] = (void *)(size_t)jit_register_count; | |
341 | |
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342 // Create CUDA context to compile and execute the kernel |
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343 int status = _cuda_cu_ctx_create(&_device_context, GRAAL_CU_CTX_MAP_HOST, _cu_device); |
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344 |
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345 if (status != GRAAL_CUDA_SUCCESS) { |
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346 tty->print_cr("[CUDA] Failed to create CUDA context for device(%d): %d", _cu_device, status); |
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347 return 0L; |
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348 } |
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349 if (TraceGPUInteraction) { |
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350 tty->print_cr("[CUDA] Success: Created context for device: %d", _cu_device); |
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351 } |
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352 |
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353 status = _cuda_cu_ctx_set_current(_device_context); |
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354 |
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355 if (status != GRAAL_CUDA_SUCCESS) { |
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356 tty->print_cr("[CUDA] Failed to set current context for device: %d", _cu_device); |
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357 return 0L; |
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358 } |
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359 if (TraceGPUInteraction) { |
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360 tty->print_cr("[CUDA] Success: Set current context for device: %d", _cu_device); |
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361 tty->print_cr("[CUDA] PTX Kernel\n%s", code); |
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362 tty->print_cr("[CUDA] Function name : %s", name); |
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363 } |
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364 |
10879 | 365 /* Load module's data with compiler options */ |
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366 status = _cuda_cu_module_load_data_ex(&cu_module, (void*) code, jit_num_options, |
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367 jit_options, (void **)jit_option_values); |
10879 | 368 if (status != GRAAL_CUDA_SUCCESS) { |
369 if (status == GRAAL_CUDA_ERROR_NO_BINARY_FOR_GPU) { | |
370 tty->print_cr("[CUDA] Check for malformed PTX kernel or incorrect PTX compilation options"); | |
371 } | |
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372 tty->print_cr("[CUDA] *** Error (%d) Failed to load module data with online compiler options for method %s", |
10879 | 373 status, name); |
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374 return 0L; |
10879 | 375 } |
376 | |
377 if (TraceGPUInteraction) { | |
378 tty->print_cr("[CUDA] Loaded data for PTX Kernel"); | |
379 } | |
380 | |
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381 struct CUfunc_st* cu_function; |
10879 | 382 status = _cuda_cu_module_get_function(&cu_function, cu_module, name); |
383 | |
384 if (status != GRAAL_CUDA_SUCCESS) { | |
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385 tty->print_cr("[CUDA] *** Error: Failed to get function %s", name); |
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386 return 0L; |
10879 | 387 } |
388 | |
389 if (TraceGPUInteraction) { | |
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390 tty->print_cr("[CUDA] Got function handle for %s kernel address %p", name, cu_function); |
10879 | 391 } |
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392 return (jlong) cu_function; |
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393 GPU_END |
10879 | 394 |
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395 // A PtxCall is used to manage executing a GPU kernel. In addition to launching |
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396 // the kernel, this class releases resources allocated for the execution. |
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397 class PtxCall: StackObj { |
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398 private: |
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399 JavaThread* _thread; // the thread on which this call is made |
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400 address _buffer; // buffer containing parameters and _return_value |
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401 int _buffer_size; // size (in bytes) of _buffer |
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402 oop* _pinned; // objects that have been pinned with cuMemHostRegister |
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403 int _pinned_length; // length of _pinned |
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404 gpu::Ptx::CUdeviceptr _ret_value; // pointer to slot in GPU memory holding the return value |
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405 int _ret_type_size; // size of the return type value |
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406 bool _ret_is_object; // specifies if the return type is Object |
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407 |
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408 bool check(int status, const char *action) { |
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409 if (status != GRAAL_CUDA_SUCCESS) { |
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410 Thread* THREAD = _thread; |
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411 char* message = NEW_RESOURCE_ARRAY_IN_THREAD(THREAD, char, O_BUFLEN + 1); |
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412 jio_snprintf(message, O_BUFLEN, "[CUDA] *** Error (status=%d): %s", status, action); |
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413 if (TraceGPUInteraction || HAS_PENDING_EXCEPTION) { |
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414 tty->print_cr(message); |
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415 } |
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416 if (!HAS_PENDING_EXCEPTION) { |
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417 SharedRuntime::throw_and_post_jvmti_exception(_thread, vmSymbols::java_lang_RuntimeException(), message); |
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418 } |
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419 return false; |
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420 } |
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421 if (TraceGPUInteraction) { |
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422 tty->print_cr("[CUDA] Success: %s", action); |
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423 } |
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424 return true; |
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425 } |
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426 |
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427 public: |
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428 PtxCall(JavaThread* thread, address buffer, int buffer_size, oop* pinned, int encodedReturnTypeSize) : _thread(thread), |
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429 _buffer(buffer), _buffer_size(buffer_size), _pinned(pinned), _pinned_length(0), _ret_value(0), _ret_is_object(encodedReturnTypeSize < 0) { |
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430 _ret_type_size = _ret_is_object ? -encodedReturnTypeSize : encodedReturnTypeSize; |
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431 } |
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432 |
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433 bool is_object_return() { return _ret_is_object; } |
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434 |
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435 void alloc_return_value() { |
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436 if (_ret_type_size != 0) { |
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437 if (check(gpu::Ptx::_cuda_cu_memalloc(&_ret_value, _ret_type_size), "Allocate device memory for return value")) { |
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438 gpu::Ptx::CUdeviceptr* retValuePtr = (gpu::Ptx::CUdeviceptr*) ((_buffer + _buffer_size) - sizeof(_ret_value)); |
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439 *retValuePtr = _ret_value; |
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440 } |
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441 } |
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442 } |
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443 |
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444 void pin_objects(int count, int* objectOffsets) { |
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445 if (count == 0) { |
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446 return; |
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447 } |
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448 for (int i = 0; i < count; i++) { |
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449 int offset = objectOffsets[i]; |
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450 oop* argPtr = (oop*) (_buffer + offset); |
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451 oop obj = *argPtr; |
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452 if (obj != NULL) { |
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453 // Size (in bytes) of object |
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454 int objSize = obj->size() * HeapWordSize; |
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455 //tty->print_cr("Pinning object %d at offset %d: %p", i, offset, obj); |
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456 if (!check(gpu::Ptx::_cuda_cu_mem_host_register(obj, objSize, GRAAL_CU_MEMHOSTREGISTER_DEVICEMAP), "Pin object")) { |
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457 return; |
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458 } |
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459 |
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460 // Record original oop so that its memory can be unpinned |
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461 _pinned[_pinned_length++] = obj; |
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462 |
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463 // Replace host pointer to object with device pointer |
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464 // to object in kernel parameters buffer |
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465 if (!check(gpu::Ptx::_cuda_cu_mem_host_get_device_pointer((gpu::Ptx::CUdeviceptr*) argPtr, obj, 0), "Get device pointer for pinned object")) { |
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466 return; |
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467 } |
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468 } |
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469 } |
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470 } |
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471 |
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472 void launch(address kernel, jint dimX, jint dimY, jint dimZ) { |
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473 // grid dimensionality |
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474 unsigned int gridX = 1; |
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475 unsigned int gridY = 1; |
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476 unsigned int gridZ = 1; |
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477 void * config[] = { |
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478 GRAAL_CU_LAUNCH_PARAM_BUFFER_POINTER, (char*) (address) _buffer, |
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479 GRAAL_CU_LAUNCH_PARAM_BUFFER_SIZE, &_buffer_size, |
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480 GRAAL_CU_LAUNCH_PARAM_END |
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481 }; |
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482 if (check(gpu::Ptx::_cuda_cu_launch_kernel((struct CUfunc_st*) (address) kernel, |
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483 gridX, gridY, gridZ, |
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484 dimX, dimY, dimZ, |
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485 0, NULL, NULL, (void**) &config), "Launch kernel")) { |
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486 } |
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487 } |
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488 |
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489 void synchronize() { |
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490 check(gpu::Ptx::_cuda_cu_ctx_synchronize(), "Synchronize kernel"); |
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491 } |
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492 |
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493 void unpin_objects() { |
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494 while (_pinned_length > 0) { |
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495 oop obj = _pinned[--_pinned_length]; |
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496 assert(obj != NULL, "npe"); |
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497 //tty->print_cr("Unpinning object %d: %p", _pinned_length, obj); |
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498 if (!check(gpu::Ptx::_cuda_cu_mem_host_unregister(obj), "Unpin object")) { |
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499 return; |
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500 } |
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501 } |
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502 } |
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503 |
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504 oop get_object_return_value() { |
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505 oop return_val; |
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506 check(gpu::Ptx::_cuda_cu_memcpy_dtoh(&return_val, _ret_value, T_OBJECT_BYTE_SIZE), "Copy return value from device"); |
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507 return return_val; |
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508 } |
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509 |
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510 jlong get_primitive_return_value() { |
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511 jlong return_val; |
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512 check(gpu::Ptx::_cuda_cu_memcpy_dtoh(&return_val, _ret_value, _ret_type_size), "Copy return value from device"); |
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513 return return_val; |
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514 } |
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515 |
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516 void free_return_value() { |
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517 if (_ret_value != 0) { |
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518 check(gpu::Ptx::_cuda_cu_memfree(_ret_value), "Free device memory"); |
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519 _ret_value = 0; |
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520 } |
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521 } |
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522 |
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523 void destroy_context() { |
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524 if (gpu::Ptx::_device_context != NULL) { |
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525 check(gpu::Ptx::_cuda_cu_ctx_destroy(gpu::Ptx::_device_context), "Destroy context"); |
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526 gpu::Ptx::_device_context = NULL; |
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527 } |
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528 } |
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529 |
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530 ~PtxCall() { |
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531 unpin_objects(); |
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532 free_return_value(); |
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533 destroy_context(); |
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534 } |
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535 }; |
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536 |
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537 GPU_VMENTRY(jlong, gpu::Ptx::get_execute_kernel_from_vm_address, (JNIEnv *env, jclass)) |
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538 return (jlong) gpu::Ptx::execute_kernel_from_vm; |
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539 GPU_END |
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540 |
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541 JRT_ENTRY(jlong, gpu::Ptx::execute_kernel_from_vm(JavaThread* thread, jlong kernel, jint dimX, jint dimY, jint dimZ, |
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542 jlong buffer, |
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543 jint bufferSize, |
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544 jint objectParametersCount, |
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545 jlong objectParametersOffsets, |
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546 jlong pinnedObjects, |
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547 int encodedReturnTypeSize)) |
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548 if (kernel == 0L) { |
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549 SharedRuntime::throw_and_post_jvmti_exception(thread, vmSymbols::java_lang_NullPointerException(), NULL); |
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550 return 0L; |
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551 } |
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552 |
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553 #if 0 |
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554 Universe::heap()->collect(GCCause::_jvmti_force_gc); |
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555 #endif |
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556 |
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557 PtxCall call(thread, (address) buffer, bufferSize, (oop*) (address) pinnedObjects, encodedReturnTypeSize); |
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558 |
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559 #define TRY(action) do { \ |
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560 action; \ |
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561 if (HAS_PENDING_EXCEPTION) return 0L; \ |
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562 } while (0) |
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563 |
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564 TRY(call.alloc_return_value()); |
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565 |
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566 TRY(call.pin_objects(objectParametersCount, (int*) (address) objectParametersOffsets)); |
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567 |
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568 TRY(call.launch((address) kernel, dimX, dimY, dimZ)); |
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569 |
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570 TRY(call.synchronize()); |
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571 |
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572 if (call.is_object_return()) { |
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573 oop return_val; |
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574 TRY(return_val = call.get_object_return_value()); |
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575 thread->set_vm_result(return_val); |
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576 return 0L; |
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577 } |
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578 |
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579 jlong return_val; |
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580 TRY(return_val = call.get_primitive_return_value()); |
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581 return return_val; |
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582 |
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583 #undef TRY |
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584 |
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585 JRT_END |
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586 |
10879 | 587 #if defined(LINUX) |
588 static const char cuda_library_name[] = "libcuda.so"; | |
589 #elif defined(__APPLE__) | |
590 static char const cuda_library_name[] = "/usr/local/cuda/lib/libcuda.dylib"; | |
591 #else | |
592 static char const cuda_library_name[] = ""; | |
593 #endif | |
594 | |
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595 bool gpu::Ptx::link() { |
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596 if (cuda_library_name == NULL) { |
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597 if (TraceGPUInteraction) { |
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598 tty->print_cr("Failed to find CUDA linkage"); |
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599 } |
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600 return false; |
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601 } |
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602 char ebuf[O_BUFLEN]; |
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603 void *handle = os::dll_load(cuda_library_name, ebuf, O_BUFLEN); |
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604 if (handle == NULL) { |
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605 if (TraceGPUInteraction) { |
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606 tty->print_cr("Unsupported CUDA platform: %s", ebuf); |
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607 } |
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608 return false; |
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609 } |
10882
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610 |
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611 LOOKUP_CUDA_FUNCTION(cuInit, cuda_cu_init); |
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612 LOOKUP_CUDA_FUNCTION(cuCtxSynchronize, cuda_cu_ctx_synchronize); |
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613 LOOKUP_CUDA_FUNCTION(cuCtxGetCurrent, cuda_cu_ctx_get_current); |
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614 LOOKUP_CUDA_FUNCTION(cuCtxSetCurrent, cuda_cu_ctx_set_current); |
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615 LOOKUP_CUDA_FUNCTION(cuDeviceGetCount, cuda_cu_device_get_count); |
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616 LOOKUP_CUDA_FUNCTION(cuDeviceGetName, cuda_cu_device_get_name); |
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617 LOOKUP_CUDA_FUNCTION(cuDeviceGet, cuda_cu_device_get); |
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618 LOOKUP_CUDA_FUNCTION(cuDeviceComputeCapability, cuda_cu_device_compute_capability); |
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619 LOOKUP_CUDA_FUNCTION(cuDeviceGetAttribute, cuda_cu_device_get_attribute); |
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620 LOOKUP_CUDA_FUNCTION(cuModuleGetFunction, cuda_cu_module_get_function); |
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621 LOOKUP_CUDA_FUNCTION(cuModuleLoadDataEx, cuda_cu_module_load_data_ex); |
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622 LOOKUP_CUDA_FUNCTION(cuLaunchKernel, cuda_cu_launch_kernel); |
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623 LOOKUP_CUDA_FUNCTION(cuMemHostRegister, cuda_cu_mem_host_register); |
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624 LOOKUP_CUDA_FUNCTION(cuMemHostUnregister, cuda_cu_mem_host_unregister); |
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625 #if defined(__x86_64) || defined(AMD64) || defined(_M_AMD64) |
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626 LOOKUP_CUDA_V2_FUNCTION(cuCtxCreate, cuda_cu_ctx_create); |
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627 LOOKUP_CUDA_V2_FUNCTION(cuCtxDestroy, cuda_cu_ctx_destroy); |
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628 LOOKUP_CUDA_V2_FUNCTION(cuMemAlloc, cuda_cu_memalloc); |
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629 LOOKUP_CUDA_V2_FUNCTION(cuMemFree, cuda_cu_memfree); |
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630 LOOKUP_CUDA_V2_FUNCTION(cuMemcpyHtoD, cuda_cu_memcpy_htod); |
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631 LOOKUP_CUDA_V2_FUNCTION(cuMemcpyDtoH, cuda_cu_memcpy_dtoh); |
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632 LOOKUP_CUDA_V2_FUNCTION(cuMemHostGetDevicePointer, cuda_cu_mem_host_get_device_pointer); |
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633 #else |
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634 LOOKUP_CUDA_FUNCTION(cuCtxCreate, cuda_cu_ctx_create); |
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635 LOOKUP_CUDA_FUNCTION(cuCtxDestroy, cuda_cu_ctx_destroy); |
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636 LOOKUP_CUDA_FUNCTION(cuMemAlloc, cuda_cu_memalloc); |
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637 LOOKUP_CUDA_FUNCTION(cuMemFree, cuda_cu_memfree); |
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638 LOOKUP_CUDA_FUNCTION(cuMemcpyHtoD, cuda_cu_memcpy_htod); |
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639 LOOKUP_CUDA_FUNCTION(cuMemcpyDtoH, cuda_cu_memcpy_dtoh); |
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640 LOOKUP_CUDA_FUNCTION(cuMemHostGetDevicePointer, cuda_cu_mem_host_get_device_pointer); |
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641 #endif |
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642 |
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643 if (TraceGPUInteraction) { |
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644 tty->print_cr("[CUDA] Success: library linkage"); |
10879 | 645 } |
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646 return true; |
10879 | 647 } |