-
Notifications
You must be signed in to change notification settings - Fork 446
/
gpu_nvidia.cpp
661 lines (618 loc) · 23.3 KB
/
gpu_nvidia.cpp
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
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
// This file is part of BOINC.
// http://boinc.berkeley.edu
// Copyright (C) 2012 University of California
//
// BOINC is free software; you can redistribute it and/or modify it
// under the terms of the GNU Lesser General Public License
// as published by the Free Software Foundation,
// either version 3 of the License, or (at your option) any later version.
//
// BOINC 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 Lesser General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public License
// along with BOINC. If not, see <http://www.gnu.org/licenses/>.
// Detection of NVIDIA GPUs
#ifdef _WIN32
#include "boinc_win.h"
/* get annotation macros from sal.h */
/* define the ones that don't exist */
#include "sal.h"
/* These are just an annotations. They don't do anything */
#ifndef __success
#define __success(x)
#endif
#ifndef __in
#define __in
#endif
#ifndef __out
#define __out
#endif
#ifndef __in_ecount
#define __in_ecount(x)
#endif
#ifndef __out_ecount
#define __out_ecount(x)
#endif
#ifndef __in_opt
#define __in_opt
#endif
#ifndef __out_opt
#define __out_opt
#endif
#ifndef __inout
#define __inout
#endif
#ifndef __inout_opt
#define __inout_opt
#endif
#ifndef __inout_ecount
#define __inout_ecount(x)
#endif
#ifndef __inout_ecount_full
#define __inout_ecount_full(x)
#endif
#ifndef __inout_ecount_part_opt
#define __inout_ecount_part_opt(x,y)
#endif
#ifndef __inout_ecount_full_opt
#define __inout_ecount_full_opt(x,y)
#endif
#ifndef __out_ecount_full_opt
#define __out_ecount_full_opt(x)
#endif
#include "nvapi.h"
#else
#ifdef __APPLE__
// Suppress obsolete warning when building for OS 10.3.9
#define DLOPEN_NO_WARN
#include <mach-o/dyld.h>
#include <Carbon/Carbon.h>
#include "hostinfo.h"
#endif
#include "config.h"
#include <dlfcn.h>
#endif
#include <vector>
#include <string>
using std::vector;
using std::string;
#include "coproc.h"
#include "util.h"
#include "client_msgs.h"
#include "gpu_detect.h"
static void get_available_nvidia_ram(COPROC_NVIDIA &cc, vector<string>& warnings);
#ifndef SIM
#if !(defined(_WIN32) || defined(__APPLE__))
static int nvidia_driver_version() {
int (*nvml_init)() = NULL;
int (*nvml_finish)() = NULL;
int (*nvml_driver)(char *f, unsigned int len) = NULL;
int dri_ver = 0;
int major=0, minor=0;
void *handle = NULL;
char driver_string[81];
handle = dlopen("libnvidia-ml.so.1", RTLD_NOW);
if (!handle) {
handle = dlopen("libnvidia-ml.so", RTLD_NOW);
if (!handle) {
goto end;
}
}
nvml_driver = (int(*)(char *, unsigned int)) dlsym(handle, "nvmlSystemGetDriverVersion");
nvml_init = (int(*)(void)) dlsym(handle, "nvmlInit");
nvml_finish = (int(*)(void)) dlsym(handle, "nvmlShutdown");
if (!nvml_driver || !nvml_init || !nvml_finish) goto end;
if (nvml_init()) goto end;
if (nvml_driver(driver_string, 80)) goto end;
sscanf(driver_string, "%d.%d", &major, &minor);
dri_ver = major*100 + std::min(minor, 99);
// minor can in fact be > 99, at least on Linux
// encoding as MMnn doesn't work.
// this is a temporary workaround.
end:
if (nvml_finish) nvml_finish();
if (handle) dlclose(handle);
return dri_ver;
}
#endif
#endif // SIM
// return 1/-1/0 if device 1 is more/less/same capable than device 2.
// factors (decreasing priority):
// - compute capability
// - software version
// - available memory
// - speed
//
// If "loose", ignore FLOPS and tolerate small memory diff
//
int nvidia_compare(COPROC_NVIDIA& c1, COPROC_NVIDIA& c2, bool loose) {
if (c1.prop.major > c2.prop.major) return 1;
if (c1.prop.major < c2.prop.major) return -1;
if (c1.prop.minor > c2.prop.minor) return 1;
if (c1.prop.minor < c2.prop.minor) return -1;
if (c1.cuda_version > c2.cuda_version) return 1;
if (c1.cuda_version < c2.cuda_version) return -1;
if (loose) {
if (c1.available_ram> 1.4*c2.available_ram) return 1;
if (c1.available_ram < .7* c2.available_ram) return -1;
return 0;
}
if (c1.available_ram > c2.available_ram) return 1;
if (c1.available_ram < c2.available_ram) return -1;
double s1 = c1.peak_flops;
double s2 = c2.peak_flops;
if (s1 > s2) return 1;
if (s1 < s2) return -1;
return 0;
}
enum CUdevice_attribute_enum {
CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK = 1,
CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X = 2,
CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Y = 3,
CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Z = 4,
CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X = 5,
CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Y = 6,
CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Z = 7,
CU_DEVICE_ATTRIBUTE_SHARED_MEMORY_PER_BLOCK = 8,
CU_DEVICE_ATTRIBUTE_TOTAL_CONSTANT_MEMORY = 9,
CU_DEVICE_ATTRIBUTE_WARP_SIZE = 10,
CU_DEVICE_ATTRIBUTE_MAX_PITCH = 11,
CU_DEVICE_ATTRIBUTE_REGISTERS_PER_BLOCK = 12,
CU_DEVICE_ATTRIBUTE_CLOCK_RATE = 13,
CU_DEVICE_ATTRIBUTE_TEXTURE_ALIGNMENT = 14,
CU_DEVICE_ATTRIBUTE_GPU_OVERLAP = 15,
CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT = 16,
CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT = 17,
CU_DEVICE_ATTRIBUTE_INTEGRATED = 18,
CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY = 19,
CU_DEVICE_ATTRIBUTE_PCI_BUS_ID = 33,
CU_DEVICE_ATTRIBUTE_PCI_DEVICE_ID = 34,
CU_DEVICE_ATTRIBUTE_PCI_DOMAIN_ID = 50
};
#ifdef _WIN32
typedef int (__stdcall *CUDA_GDC)(int *count);
typedef int (__stdcall *CUDA_GDV)(int* version);
typedef int (__stdcall *CUDA_GDI)(unsigned int);
typedef int (__stdcall *CUDA_GDG)(int*, int);
typedef int (__stdcall *CUDA_GDA)(int*, int, int);
typedef int (__stdcall *CUDA_GDN)(char*, int, int);
typedef int (__stdcall *CUDA_GDM)(size_t*, int);
typedef int (__stdcall *CUDA_GDCC)(int*, int*, int);
typedef int (__stdcall *CUDA_CC)(void**, unsigned int, unsigned int);
typedef int (__stdcall *CUDA_CD)(void*);
typedef int (__stdcall *CUDA_MA)(unsigned int*, size_t);
typedef int (__stdcall *CUDA_MF)(unsigned int);
typedef int (__stdcall *CUDA_MGI)(size_t*, size_t*);
CUDA_GDC p_cuDeviceGetCount = NULL;
CUDA_GDV p_cuDriverGetVersion = NULL;
CUDA_GDI p_cuInit = NULL;
CUDA_GDG p_cuDeviceGet = NULL;
CUDA_GDA p_cuDeviceGetAttribute = NULL;
CUDA_GDN p_cuDeviceGetName = NULL;
CUDA_GDM p_cuDeviceTotalMem = NULL;
CUDA_GDM p_cuDeviceTotalMem_v2 = NULL;
CUDA_GDCC p_cuDeviceComputeCapability = NULL;
CUDA_CC p_cuCtxCreate = NULL;
CUDA_CD p_cuCtxDestroy = NULL;
CUDA_MA p_cuMemAlloc = NULL;
CUDA_MF p_cuMemFree = NULL;
CUDA_MGI p_cuMemGetInfo = NULL;
CUDA_MGI p_cuMemGetInfo_v2 = NULL;
#else
int (*p_cuInit)(unsigned int);
int (*p_cuDeviceGetCount)(int*);
int (*p_cuDriverGetVersion)(int*);
int (*p_cuDeviceGet)(int*, int);
int (*p_cuDeviceGetAttribute)(int*, int, int);
int (*p_cuDeviceGetName)(char*, int, int);
int (*p_cuDeviceTotalMem)(size_t*, int);
int (*p_cuDeviceTotalMem_v2)(size_t*, int);
int (*p_cuDeviceComputeCapability)(int*, int*, int);
int (*p_cuCtxCreate)(void**, unsigned int, unsigned int);
int (*p_cuCtxDestroy)(void*);
int (*p_cuMemAlloc)(unsigned int*, size_t);
int (*p_cuMemFree)(unsigned int);
int (*p_cuMemGetInfo)(size_t*, size_t*);
int (*p_cuMemGetInfo_v2)(size_t*, size_t*);
#endif
// NVIDIA interfaces are documented here:
// http://developer.download.nvidia.com/compute/cuda/2_3/toolkit/docs/online/index.html
void COPROC_NVIDIA::get(
vector<string>& warnings
) {
int cuda_ndevs, retval;
char buf[2048];
int j, itemp;
size_t global_mem = 0;
string s;
COPROC_NVIDIA cc;
#ifdef _WIN32
HMODULE cudalib = LoadLibrary("nvcuda.dll");
if (!cudalib) {
gpu_warning(warnings, "No NVIDIA library found");
return;
}
p_cuDeviceGetCount = (CUDA_GDC)GetProcAddress( cudalib, "cuDeviceGetCount" );
p_cuDriverGetVersion = (CUDA_GDV)GetProcAddress( cudalib, "cuDriverGetVersion" );
p_cuInit = (CUDA_GDI)GetProcAddress( cudalib, "cuInit" );
p_cuDeviceGet = (CUDA_GDG)GetProcAddress( cudalib, "cuDeviceGet" );
p_cuDeviceGetAttribute = (CUDA_GDA)GetProcAddress( cudalib, "cuDeviceGetAttribute" );
p_cuDeviceGetName = (CUDA_GDN)GetProcAddress( cudalib, "cuDeviceGetName" );
p_cuDeviceTotalMem = (CUDA_GDM)GetProcAddress( cudalib, "cuDeviceTotalMem" );
p_cuDeviceTotalMem_v2 = (CUDA_GDM)GetProcAddress(cudalib, "cuDeviceTotalMem_v2");
p_cuDeviceComputeCapability = (CUDA_GDCC)GetProcAddress( cudalib, "cuDeviceComputeCapability" );
p_cuCtxCreate = (CUDA_CC)GetProcAddress( cudalib, "cuCtxCreate" );
p_cuCtxDestroy = (CUDA_CD)GetProcAddress( cudalib, "cuCtxDestroy" );
p_cuMemAlloc = (CUDA_MA)GetProcAddress( cudalib, "cuMemAlloc" );
p_cuMemFree = (CUDA_MF)GetProcAddress( cudalib, "cuMemFree" );
p_cuMemGetInfo = (CUDA_MGI)GetProcAddress(cudalib, "cuMemGetInfo");
p_cuMemGetInfo_v2 = (CUDA_MGI)GetProcAddress(cudalib, "cuMemGetInfo_v2");
#ifndef SIM
NvAPI_Initialize();
NvAPI_ShortString ss;
NvU32 Version = 0;
NvAPI_SYS_GetDriverAndBranchVersion(&Version, ss);
#if 0
// NvAPI now provides an API for getting #cores :-)
// But not FLOPs per clock cycle :-(
// Anyway, don't use this for now because server code estimates FLOPS
// based on compute capability, so we may as well do the same
// See http://docs.nvidia.com/gameworks/content/gameworkslibrary/coresdk/nvapi/
//
NvPhysicalGpuHandle GPUHandle[NVAPI_MAX_PHYSICAL_GPUS];
NvU32 GpuCount, nc;
NvAPI_EnumPhysicalGPUs(GPUHandle, &GpuCount);
for (unsigned int i=0; i<GpuCount; i++) {
NvAPI_GPU_GetGpuCoreCount(GPUHandle[i], &nc);
}
#endif
#endif
#else
void* cudalib = NULL;
#ifdef __APPLE__
cudalib = dlopen("/usr/local/cuda/lib/libcuda.dylib", RTLD_NOW);
#else
cudalib = dlopen("libcuda.so", RTLD_NOW);
#endif
if (!cudalib) {
snprintf(buf, sizeof(buf), "NVIDIA: %s", dlerror());
gpu_warning(warnings, buf);
return;
}
p_cuDeviceGetCount = (int(*)(int*)) dlsym(cudalib, "cuDeviceGetCount");
p_cuDriverGetVersion = (int(*)(int*)) dlsym( cudalib, "cuDriverGetVersion" );
p_cuInit = (int(*)(unsigned int)) dlsym( cudalib, "cuInit" );
p_cuDeviceGet = (int(*)(int*, int)) dlsym( cudalib, "cuDeviceGet" );
p_cuDeviceGetAttribute = (int(*)(int*, int, int)) dlsym( cudalib, "cuDeviceGetAttribute" );
p_cuDeviceGetName = (int(*)(char*, int, int)) dlsym( cudalib, "cuDeviceGetName" );
p_cuDeviceTotalMem = (int(*)(size_t*, int)) dlsym( cudalib, "cuDeviceTotalMem" );
p_cuDeviceTotalMem_v2 = (int(*)(size_t*, int)) dlsym(cudalib, "cuDeviceTotalMem_v2");
p_cuDeviceComputeCapability = (int(*)(int*, int*, int)) dlsym( cudalib, "cuDeviceComputeCapability" );
p_cuCtxCreate = (int(*)(void**, unsigned int, unsigned int)) dlsym( cudalib, "cuCtxCreate" );
p_cuCtxDestroy = (int(*)(void*)) dlsym( cudalib, "cuCtxDestroy" );
p_cuMemAlloc = (int(*)(unsigned int*, size_t)) dlsym( cudalib, "cuMemAlloc" );
p_cuMemFree = (int(*)(unsigned int)) dlsym( cudalib, "cuMemFree" );
p_cuMemGetInfo = (int(*)(size_t*, size_t*)) dlsym( cudalib, "cuMemGetInfo" );
p_cuMemGetInfo_v2 = (int(*)(size_t*, size_t*)) dlsym(cudalib, "cuMemGetInfo_v2");
#endif
if (!p_cuDriverGetVersion) {
gpu_warning(warnings, "cuDriverGetVersion() missing from NVIDIA library");
goto leave;
}
if (!p_cuInit) {
gpu_warning(warnings, "cuInit() missing from NVIDIA library");
goto leave;
}
if (!p_cuDeviceGetCount) {
gpu_warning(warnings, "cuDeviceGetCount() missing from NVIDIA library");
goto leave;
}
if (!p_cuDeviceGet) {
gpu_warning(warnings, "cuDeviceGet() missing from NVIDIA library");
goto leave;
}
if (!p_cuDeviceGetAttribute) {
gpu_warning(warnings, "cuDeviceGetAttribute() missing from NVIDIA library");
goto leave;
}
if (!p_cuDeviceTotalMem && !p_cuDeviceTotalMem_v2) {
gpu_warning(warnings, "cuDeviceTotalMem() missing from NVIDIA library");
goto leave;
}
if (!p_cuDeviceComputeCapability) {
gpu_warning(warnings, "cuDeviceComputeCapability() missing from NVIDIA library");
goto leave;
}
if (!p_cuMemAlloc) {
gpu_warning(warnings, "cuMemAlloc() missing from NVIDIA library");
goto leave;
}
if (!p_cuMemFree) {
gpu_warning(warnings, "cuMemFree() missing from NVIDIA library");
goto leave;
}
retval = (*p_cuInit)(0);
#ifdef __APPLE__
// If system is just booting, CUDA driver may not be ready yet
if (retval) {
if (get_system_uptime() < 300) { // Retry only if system has been up for under 5 minutes
for (int retryCount=0; retryCount<120; retryCount++) {
retval = (*p_cuInit)(0);
if (!retval) break;
boinc_sleep(1.);
continue;
}
}
}
#endif
if (retval) {
snprintf(buf, sizeof(buf), "NVIDIA drivers present but no GPUs found");
gpu_warning(warnings, buf);
goto leave;
}
retval = (*p_cuDriverGetVersion)(&cuda_version);
if (retval) {
snprintf(buf, sizeof(buf), "cuDriverGetVersion() returned %d", retval);
gpu_warning(warnings, buf);
goto leave;
}
have_cuda = true;
retval = (*p_cuDeviceGetCount)(&cuda_ndevs);
if (retval) {
snprintf(buf, sizeof(buf), "cuDeviceGetCount() returned %d", retval);
gpu_warning(warnings, buf);
goto leave;
}
snprintf(buf, sizeof(buf), "NVIDIA library reports %d GPU%s", cuda_ndevs, (cuda_ndevs==1)?"":"s");
gpu_warning(warnings, buf);
for (j=0; j<cuda_ndevs; j++) {
cc.prop.clear();
CUdevice device;
retval = (*p_cuDeviceGet)(&device, j);
if (retval) {
snprintf(buf, sizeof(buf), "cuDeviceGet(%d) returned %d", j, retval);
gpu_warning(warnings, buf);
goto leave;
}
retval = (*p_cuDeviceGetName)(cc.prop.name, 256, device);
if (retval) {
snprintf(buf, sizeof(buf), "cuDeviceGetName(%d) returned %d", j, retval);
gpu_warning(warnings, buf);
goto leave;
}
(*p_cuDeviceComputeCapability)(&cc.prop.major, &cc.prop.minor, device);
if (p_cuDeviceTotalMem_v2) {
(*p_cuDeviceTotalMem_v2)(&global_mem, device);
} else {
(*p_cuDeviceTotalMem)(&global_mem, device);
}
cc.prop.totalGlobalMem = (double) global_mem;
(*p_cuDeviceGetAttribute)(&itemp, CU_DEVICE_ATTRIBUTE_SHARED_MEMORY_PER_BLOCK, device);
cc.prop.sharedMemPerBlock = (double) itemp;
(*p_cuDeviceGetAttribute)(&cc.prop.regsPerBlock, CU_DEVICE_ATTRIBUTE_REGISTERS_PER_BLOCK, device);
(*p_cuDeviceGetAttribute)(&cc.prop.warpSize, CU_DEVICE_ATTRIBUTE_WARP_SIZE, device);
(*p_cuDeviceGetAttribute)(&itemp, CU_DEVICE_ATTRIBUTE_MAX_PITCH, device);
cc.prop.memPitch = (double) itemp;
retval = (*p_cuDeviceGetAttribute)(&cc.prop.maxThreadsPerBlock, CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK, device);
retval = (*p_cuDeviceGetAttribute)(&cc.prop.maxThreadsDim[0], CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X, device);
(*p_cuDeviceGetAttribute)(&cc.prop.maxThreadsDim[1], CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Y, device);
(*p_cuDeviceGetAttribute)(&cc.prop.maxThreadsDim[2], CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Z, device);
(*p_cuDeviceGetAttribute)(&cc.prop.maxGridSize[0], CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X, device);
(*p_cuDeviceGetAttribute)(&cc.prop.maxGridSize[1], CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Y, device);
(*p_cuDeviceGetAttribute)(&cc.prop.maxGridSize[2], CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Z, device);
(*p_cuDeviceGetAttribute)(&cc.prop.clockRate, CU_DEVICE_ATTRIBUTE_CLOCK_RATE, device);
(*p_cuDeviceGetAttribute)(&itemp, CU_DEVICE_ATTRIBUTE_TOTAL_CONSTANT_MEMORY, device);
cc.prop.totalConstMem = (double) itemp;
(*p_cuDeviceGetAttribute)(&itemp, CU_DEVICE_ATTRIBUTE_TEXTURE_ALIGNMENT, device);
cc.prop.textureAlignment = (double) itemp;
(*p_cuDeviceGetAttribute)(&cc.prop.deviceOverlap, CU_DEVICE_ATTRIBUTE_GPU_OVERLAP, device);
(*p_cuDeviceGetAttribute)(&cc.prop.multiProcessorCount, CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT, device);
(*p_cuDeviceGetAttribute)(&cc.pci_info.bus_id, CU_DEVICE_ATTRIBUTE_PCI_BUS_ID, device);
(*p_cuDeviceGetAttribute)(&cc.pci_info.device_id, CU_DEVICE_ATTRIBUTE_PCI_DEVICE_ID, device);
(*p_cuDeviceGetAttribute)(&cc.pci_info.domain_id, CU_DEVICE_ATTRIBUTE_PCI_DOMAIN_ID, device);
if (cc.prop.major <= 0) continue; // major == 0 means emulation
if (cc.prop.major > 100) continue; // e.g. 9999 is an error
#ifdef SIM
cc.display_driver_version = 0;
#elif defined(_WIN32)
cc.display_driver_version = Version;
#elif defined(__APPLE__)
cc.display_driver_version = NSVersionOfRunTimeLibrary("cuda");
#else
cc.display_driver_version = nvidia_driver_version();
#endif
cc.have_cuda = true;
cc.cuda_version = cuda_version;
cc.device_num = j;
cc.set_peak_flops();
if (cc.bad_gpu_peak_flops("CUDA", s)) {
gpu_warning(warnings, s.c_str());
}
get_available_nvidia_ram(cc, warnings);
nvidia_gpus.push_back(cc);
}
if (!nvidia_gpus.size()) {
gpu_warning(warnings, "No CUDA-capable NVIDIA GPUs found");
}
leave:
#ifdef _WIN32
if (cudalib) FreeLibrary(cudalib);
#else
if (cudalib) dlclose(cudalib);
#endif
}
// Find the most capable instance; copy to *this.
// set is_used (USED, UNUSED, IGNORED) for each instance.
// Don't use less-capable instances (unless use_all is set)
//
void COPROC_NVIDIA::correlate(
bool use_all, // if false, use only those equivalent to most capable
vector<int>& ignore_devs
) {
unsigned int i;
if (!nvidia_gpus.size()) return;
// identify the most capable non-ignored instance
//
bool first = true;
for (i=0; i<nvidia_gpus.size(); i++) {
nvidia_gpus[i].is_used = COPROC_IGNORED;
if (in_vector(nvidia_gpus[i].device_num, ignore_devs)) continue;
#ifdef __APPLE__
if ((nvidia_gpus[i].cuda_version >= 6050) && nvidia_gpus[i].prop.major < 2) {
// Can't use GPUs with compute capability < 2 with CUDA drivers >= 6.5.x
nvidia_gpus[i].is_used = COPROC_UNUSED;
continue;
}
#endif
if (first) {
*this = nvidia_gpus[i];
first = false;
} else if (nvidia_compare(nvidia_gpus[i], *this, false) > 0) {
*this = nvidia_gpus[i];
}
}
// see which other instances are equivalent,
// and set "count", "device_nums", and "pci_infos"
//
count = 0;
for (i=0; i<nvidia_gpus.size(); i++) {
if (in_vector(nvidia_gpus[i].device_num, ignore_devs)) {
nvidia_gpus[i].is_used = COPROC_IGNORED;
} else if (this->have_opencl && !nvidia_gpus[i].have_opencl) {
nvidia_gpus[i].is_used = COPROC_UNUSED;
} else if (this->have_cuda && !nvidia_gpus[i].have_cuda) {
nvidia_gpus[i].is_used = COPROC_UNUSED;
#ifdef __APPLE__
} else if (nvidia_gpus[i].is_used == COPROC_UNUSED) {
// Can't use GPUs with compute capability < 2 with CUDA drivers >= 6.5.x
continue;
#endif
} else if (use_all || !nvidia_compare(nvidia_gpus[i], *this, true)) {
device_nums[count] = nvidia_gpus[i].device_num;
pci_infos[count] = nvidia_gpus[i].pci_info;
count++;
nvidia_gpus[i].is_used = COPROC_USED;
} else {
nvidia_gpus[i].is_used = COPROC_UNUSED;
}
}
}
// See how much RAM is available on this GPU.
//
// CAUTION: as currently written, this method should be
// called only from COPROC_NVIDIA::get(). If in the
// future you wish to call it from additional places:
// * It must be called from a separate child process on
// dual-GPU laptops (e.g., Macbook Pros) with the results
// communicated to the main client process via IPC or a
// temp file. See the comments about dual-GPU laptops
// in gpu_detect.cpp and main.cpp for more details.
// * The CUDA library must be loaded and cuInit() called
// first.
// * See client/coproc_detect.cpp and cpu_sched.cpp in
// BOINC 6.12.36 for an earlier attempt to call this
// from the scheduler. Note that it was abandoned
// due to repeated calls crashing the driver.
//
static void get_available_nvidia_ram(COPROC_NVIDIA &cc, vector<string>& warnings) {
int retval;
size_t memfree = 0, memtotal = 0;
int device;
void* ctx;
char buf[256];
cc.available_ram = cc.prop.totalGlobalMem;
if (!p_cuDeviceGet) {
gpu_warning(warnings, "cuDeviceGet() missing from NVIDIA library");
return;
}
if (!p_cuCtxCreate) {
gpu_warning(warnings, "cuCtxCreate() missing from NVIDIA library");
return;
}
if (!p_cuCtxDestroy) {
gpu_warning(warnings, "cuCtxDestroy() missing from NVIDIA library");
return;
}
if (!p_cuMemGetInfo && !p_cuMemGetInfo_v2) {
gpu_warning(warnings, "cuMemGetInfo() missing from NVIDIA library");
return;
}
retval = (*p_cuDeviceGet)(&device, cc.device_num);
if (retval) {
snprintf(buf, sizeof(buf),
"[coproc] cuDeviceGet(%d) returned %d", cc.device_num, retval
);
gpu_warning(warnings, buf);
return;
}
retval = (*p_cuCtxCreate)(&ctx, 0, device);
if (retval) {
snprintf(buf, sizeof(buf),
"[coproc] cuCtxCreate(%d) returned %d", cc.device_num, retval
);
gpu_warning(warnings, buf);
return;
}
if (p_cuMemGetInfo_v2) {
retval = (*p_cuMemGetInfo_v2)(&memfree, &memtotal);
}
else {
retval = (*p_cuMemGetInfo)(&memfree, &memtotal);
}
if (retval) {
snprintf(buf, sizeof(buf),
"[coproc] cuMemGetInfo(%d) returned %d", cc.device_num, retval
);
gpu_warning(warnings, buf);
(*p_cuCtxDestroy)(ctx);
return;
}
(*p_cuCtxDestroy)(ctx);
cc.available_ram = (double) memfree;
}
// check whether each GPU is running a graphics app (assume yes)
// return true if there's been a change since last time
//
// CAUTION: this method is not currently used. If you wish
// to call it in the future:
// * It must be called from a separate child process on
// dual-GPU laptops (e.g., Macbook Pros) with the results
// communicated to the main client process via IPC or a
// temp file. See the comments about dual-GPU laptops
// in gpu_detect.cpp and main.cpp for more details.
// * The CUDA library must be loaded and cuInit() called
// first.
//
#if 0
bool COPROC_NVIDIA::check_running_graphics_app() {
int retval, j;
bool change = false;
if (!p_cuDeviceGet) {
gpu_warning(warnings, "cuDeviceGet() missing from NVIDIA library");
return;
}
if (!p_cuDeviceGetAttribute) {
gpu_warning(warnings, "cuDeviceGetAttribute() missing from NVIDIA library");
return;
}
for (j=0; j<count; j++) {
bool new_val = true;
int device, kernel_timeout;
retval = (*p_cuDeviceGet)(&device, j);
if (!retval) {
retval = (*p_cuDeviceGetAttribute)(&kernel_timeout, CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT, device);
if (!retval && !kernel_timeout) {
new_val = false;
}
}
if (new_val != running_graphics_app[j]) {
change = true;
}
running_graphics_app[j] = new_val;
}
return change;
}
#endif