1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
|
// Adopted from OpenSubdiv with the following license:
//
// Copyright 2015 Pixar
//
// Licensed under the Apache License, Version 2.0 (the "Apache License")
// with the following modification; you may not use this file except in
// compliance with the Apache License and the following modification to it:
// Section 6. Trademarks. is deleted and replaced with:
//
// 6. Trademarks. This License does not grant permission to use the trade
// names, trademarks, service marks, or product names of the Licensor
// and its affiliates, except as required to comply with Section 4(c) of
// the License and to reproduce the content of the NOTICE file.
//
// You may obtain a copy of the Apache License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the Apache License with the above modification is
// distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied. See the Apache License for the specific
// language governing permissions and limitations under the Apache License.
#ifdef OPENSUBDIV_HAS_CUDA
#ifdef _MSC_VER
# include <iso646.h>
#endif
#include "opensubdiv_device_context_cuda.h"
#if defined(_WIN32)
# include <windows.h>
#elif defined(__APPLE__)
# include <OpenGL/OpenGL.h>
#else
# include <GL/glx.h>
# include <X11/Xlib.h>
#endif
#include <cuda.h>
#include <cuda_gl_interop.h>
#include <cuda_runtime_api.h>
#include <algorithm>
#include <cstdio>
#define message(fmt, ...)
// #define message(fmt, ...) fprintf(stderr, fmt, __VA_ARGS__)
#define error(fmt, ...) fprintf(stderr, fmt, __VA_ARGS__)
namespace {
int getCudaDeviceForCurrentGLContext() {
// Find and use the CUDA device for the current GL context
unsigned int interop_device_count = 0;
int interopDevices[1];
cudaError_t status = cudaGLGetDevices(&interop_device_count,
interopDevices,
1,
cudaGLDeviceListCurrentFrame);
if (status == cudaErrorNoDevice || interop_device_count != 1) {
message("CUDA no interop devices found.\n");
return 0;
}
int device = interopDevices[0];
#if defined(_WIN32)
return device;
#elif defined(__APPLE__)
return device;
#else // X11
Display* display = glXGetCurrentDisplay();
int screen = DefaultScreen(display);
if (device != screen) {
error("The CUDA interop device (%d) does not match "
"the screen used by the current GL context (%d), "
"which may cause slow performance on systems "
"with multiple GPU devices.",
device, screen);
}
message("CUDA init using device for current GL context: %d\n", device);
return device;
#endif
}
// Beginning of GPU Architecture definitions.
int convertSMVer2Cores_local(int major, int minor) {
// Defines for GPU Architecture types (using the SM version to determine
// the # of cores per SM
typedef struct {
int SM; // 0xMm (hexidecimal notation),
// M = SM Major version,
// and m = SM minor version
int Cores;
} sSMtoCores;
sSMtoCores nGpuArchCoresPerSM[] = {
{0x10, 8}, // Tesla Generation (SM 1.0) G80 class.
{0x11, 8}, // Tesla Generation (SM 1.1) G8x class.
{0x12, 8}, // Tesla Generation (SM 1.2) G9x class.
{0x13, 8}, // Tesla Generation (SM 1.3) GT200 class.
{0x20, 32}, // Fermi Generation (SM 2.0) GF100 class.
{0x21, 48}, // Fermi Generation (SM 2.1) GF10x class.
{0x30, 192}, // Fermi Generation (SM 3.0) GK10x class.
{-1, -1}};
int index = 0;
while (nGpuArchCoresPerSM[index].SM != -1) {
if (nGpuArchCoresPerSM[index].SM == ((major << 4) + minor)) {
return nGpuArchCoresPerSM[index].Cores;
}
index++;
}
printf("MapSMtoCores undefined SMversion %d.%d!\n", major, minor);
return -1;
}
// This function returns the best GPU (with maximum GFLOPS).
int cutGetMaxGflopsDeviceId() {
int current_device = 0, sm_per_multiproc = 0;
int max_compute_perf = 0, max_perf_device = -1;
int device_count = 0, best_SM_arch = 0;
int compat_major, compat_minor;
cuDeviceGetCount(&device_count);
// Find the best major SM Architecture GPU device.
while (current_device < device_count) {
cuDeviceComputeCapability(&compat_major, &compat_minor, current_device);
if (compat_major > 0 && compat_major < 9999) {
best_SM_arch = std::max(best_SM_arch, compat_major);
}
current_device++;
}
// Find the best CUDA capable GPU device.
current_device = 0;
while (current_device < device_count) {
cuDeviceComputeCapability(&compat_major, &compat_minor, current_device);
if (compat_major == 9999 && compat_minor == 9999) {
sm_per_multiproc = 1;
} else {
sm_per_multiproc = convertSMVer2Cores_local(compat_major, compat_minor);
}
int multi_processor_count;
cuDeviceGetAttribute(&multi_processor_count,
CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT,
current_device);
int clock_rate;
cuDeviceGetAttribute(&clock_rate, CU_DEVICE_ATTRIBUTE_CLOCK_RATE,
current_device);
int compute_perf = multi_processor_count * sm_per_multiproc * clock_rate;
if (compute_perf > max_compute_perf) {
/* If we find GPU with SM major > 2, search only these */
if (best_SM_arch > 2) {
/* If our device==dest_SM_arch, choose this, or else pass. */
if (compat_major == best_SM_arch) {
max_compute_perf = compute_perf;
max_perf_device = current_device;
}
} else {
max_compute_perf = compute_perf;
max_perf_device = current_device;
}
}
++current_device;
}
return max_perf_device;
}
} // namespace
bool CudaDeviceContext::HAS_CUDA_VERSION_4_0() {
#ifdef OPENSUBDIV_HAS_CUDA
static bool cuda_initialized = false;
static bool cuda_load_success = true;
if (!cuda_initialized) {
cuda_initialized = true;
#ifdef OPENSUBDIV_HAS_CUEW
cuda_load_success = cuewInit(CUEW_INIT_CUDA) == CUEW_SUCCESS;
if (!cuda_load_success) {
fprintf(stderr, "Loading CUDA failed.\n");
}
#endif
// Need to initialize CUDA here so getting device
// with the maximum FPLOS works fine.
if (cuInit(0) == CUDA_SUCCESS) {
// This is to deal with cases like NVidia Optimus,
// when there might be CUDA library installed but
// NVidia card is not being active.
if (cutGetMaxGflopsDeviceId() < 0) {
cuda_load_success = false;
}
} else {
cuda_load_success = false;
}
}
return cuda_load_success;
#else
return false;
#endif
}
CudaDeviceContext::CudaDeviceContext()
: initialized_(false) {
}
CudaDeviceContext::~CudaDeviceContext() {
cudaDeviceReset();
}
bool CudaDeviceContext::Initialize() {
// See if any cuda device is available.
int device_count = 0;
cudaGetDeviceCount(&device_count);
message("CUDA device count: %d\n", device_count);
if (device_count <= 0) {
return false;
}
cudaGLSetGLDevice(getCudaDeviceForCurrentGLContext());
initialized_ = true;
return true;
}
bool CudaDeviceContext::IsInitialized() const {
return initialized_;
}
#endif // OPENSUBDIV_HAS_CUDA
|
