This repository has been archived by the owner on Mar 18, 2020. It is now read-only.
forked from BeamMW/opencl-miner
-
Notifications
You must be signed in to change notification settings - Fork 0
/
clHost.cpp
476 lines (375 loc) · 18.7 KB
/
clHost.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
// BEAM OpenCL Miner
// OpenCL Host Interface
// Copyright 2018 The Beam Team
// Copyright 2018 Wilke Trei
#include "clHost.h"
#include "./kernels/equihash_150_5_inc.h"
namespace beamMiner {
// Helper functions to split a string
inline vector<string> &split(const string &s, char delim, vector<string> &elems) {
stringstream ss(s);
string item;
while(getline(ss, item, delim)) {
elems.push_back(item);
}
return elems;
}
inline vector<string> split(const string &s, char delim) {
vector<string> elems;
return split(s, delim, elems);
}
// Helper function that tests if a OpenCL device supports a certain CL extension
inline bool hasExtension(cl::Device &device, string extension) {
string info;
device.getInfo(CL_DEVICE_EXTENSIONS, &info);
vector<string> extens = split(info, ' ');
for (int i=0; i<extens.size(); i++) {
if (extens[i].compare(extension) == 0) return true;
}
return false;
}
// This is a bit ugly c-style, but the OpenCL headers are initially for c and
// support c-style callback functions (no member functions) only.
// This function will be called every time a GPU is done with its current work
void CL_CALLBACK CCallbackFunc(cl_event ev, cl_int err , void* data) {
clHost* self = static_cast<clHost*>(((clCallbackData*) data)->host);
self->callbackFunc(err,data);
}
// Function to load the OpenCL kernel and prepare our device for mining
void clHost::loadAndCompileKernel(cl::Device &device, uint32_t pl, bool use3G) {
cout << " Loading and compiling Beam OpenCL Kernel" << endl;
// reading the kernel
string progStr = string(__equihash_150_5_cl, __equihash_150_5_cl_len);
/* ifstream file("./kernels/equihash_150_5.cl");
string progStr(istreambuf_iterator<char>(file),(istreambuf_iterator<char>())); */
cl::Program::Sources source(1,std::make_pair(progStr.c_str(), progStr.length()+1));
// Create a program object and build it
vector<cl::Device> devicesTMP;
devicesTMP.push_back(device);
cl::Program program(contexts[pl], source);
cl_int err;
if (!use3G) {
err = program.build(devicesTMP,"");
} else {
err = program.build(devicesTMP,"-DMEM3G");
}
// Check if the build was Ok
if (!err) {
cout << " Build sucessfull. " << endl;
// Store the device and create a queue for it
cl_command_queue_properties queue_prop = 0;
devices.push_back(device);
queues.push_back(cl::CommandQueue(contexts[pl], devices[devices.size()-1], queue_prop, NULL));
// Reserve events, space for storing results and so on
events.push_back(cl::Event());
results.push_back(NULL);
currentWork.push_back(clCallbackData());
paused.push_back(true);
is3G.push_back(use3G);
solutionCnt.push_back(0);
// Create the kernels
vector<cl::Kernel> newKernels;
newKernels.push_back(cl::Kernel(program, "clearCounter", &err));
newKernels.push_back(cl::Kernel(program, "round0", &err));
newKernels.push_back(cl::Kernel(program, "round1", &err));
newKernels.push_back(cl::Kernel(program, "round2", &err));
newKernels.push_back(cl::Kernel(program, "round3", &err));
newKernels.push_back(cl::Kernel(program, "round4", &err));
newKernels.push_back(cl::Kernel(program, "round5", &err));
if (use3G) {
newKernels.push_back(cl::Kernel(program, "combine3G", &err));
newKernels.push_back(cl::Kernel(program, "repack", &err));
newKernels.push_back(cl::Kernel(program, "move", &err));
} else {
newKernels.push_back(cl::Kernel(program, "combine", &err));
}
kernels.push_back(newKernels);
// Create the buffers
vector<cl::Buffer> newBuffers;
if (!use3G) {
newBuffers.push_back(cl::Buffer(contexts[pl], CL_MEM_READ_WRITE, sizeof(cl_uint4) * 71303168, NULL, &err));
newBuffers.push_back(cl::Buffer(contexts[pl], CL_MEM_READ_WRITE, sizeof(cl_uint4) * 71303168, NULL, &err));
newBuffers.push_back(cl::Buffer(contexts[pl], CL_MEM_READ_WRITE, sizeof(cl_uint4) * 71303168, NULL, &err));
newBuffers.push_back(cl::Buffer(contexts[pl], CL_MEM_READ_WRITE, sizeof(cl_uint2) * 71303168, NULL, &err));
} else {
newBuffers.push_back(cl::Buffer(contexts[pl], CL_MEM_READ_WRITE, sizeof(cl_uint4) * 69599232, NULL, &err));
newBuffers.push_back(cl::Buffer(contexts[pl], CL_MEM_READ_WRITE, sizeof(cl_uint4) * 69599232, NULL, &err));
newBuffers.push_back(cl::Buffer(contexts[pl], CL_MEM_READ_WRITE, sizeof(cl_uint4) * 52199424, NULL, &err));
newBuffers.push_back(cl::Buffer(contexts[pl], CL_MEM_READ_WRITE, sizeof(cl_uint2) * 1, NULL, &err));
}
newBuffers.push_back(cl::Buffer(contexts[pl], CL_MEM_READ_WRITE, sizeof(cl_uint4) * 256, NULL, &err));
newBuffers.push_back(cl::Buffer(contexts[pl], CL_MEM_READ_WRITE, sizeof(cl_uint) * 49152, NULL, &err));
newBuffers.push_back(cl::Buffer(contexts[pl], CL_MEM_READ_WRITE, sizeof(cl_uint) * 324, NULL, &err));
buffers.push_back(newBuffers);
} else {
cout << " Program build error, device will not be used. " << endl;
// Print error msg so we can debug the kernel source
cout << " Build Log: " << program.getBuildInfo<CL_PROGRAM_BUILD_LOG>(devicesTMP[0]) << endl;
}
}
// Detect the OpenCL hardware on this system
void clHost::detectPlatFormDevices(vector<int32_t> selDev, bool allowCPU, bool force3G) {
// read the OpenCL platforms on this system
cl::Platform::get(&platforms);
// this is for enumerating the devices
uint32_t curDiv = 0;
uint32_t selNum = 0;
for (int pl=0; pl<platforms.size(); pl++) {
// Create the OpenCL contexts, one for each platform
cl_context_properties properties[] = { CL_CONTEXT_PLATFORM, (cl_context_properties)platforms[pl](), 0};
cl::Context context;
if (allowCPU) {
context = cl::Context(CL_DEVICE_TYPE_ALL, properties);
} else {
context = cl::Context(CL_DEVICE_TYPE_GPU, properties);
}
contexts.push_back(context);
// Read the devices of this platform
vector< cl::Device > nDev = context.getInfo<CL_CONTEXT_DEVICES>();
for (uint32_t di=0; di<nDev.size(); di++) {
// Print the device name
string name;
if ( hasExtension(nDev[di], "cl_amd_device_attribute_query") ) {
nDev[di].getInfo(0x4038,&name); // on AMD this gives more readable result
} else {
nDev[di].getInfo(CL_DEVICE_NAME, &name); // for all other GPUs
}
// Get rid of strange characters at the end of device name
if (isalnum((int) name.back()) == 0) {
name.pop_back();
}
cout << "Found device " << curDiv << ": " << name << endl;
// Check if the device should be selected
bool pick = false;
if (selDev[0] == -1) pick = true;
if (selNum < selDev.size()) {
if (curDiv == selDev[selNum]) {
pick = true;
selNum++;
}
}
if (pick) {
// Check if the CPU / GPU has enough memory
uint64_t deviceMemory = nDev[di].getInfo<CL_DEVICE_GLOBAL_MEM_SIZE>();
uint64_t needed_4G = 7* ((uint64_t) 570425344) + 4096 + 196608 + 1296;
uint64_t needed_3G = 4* ((uint64_t) 556793856) + ((uint64_t) 835190784) + 4096 + 196608 + 1296;
cout << " Device reports " << deviceMemory / (1024*1024) << "MByte total memory" << endl;
if ( hasExtension(nDev[di], "cl_amd_device_attribute_query") ) {
uint64_t freeDeviceMemory;
nDev[di].getInfo(0x4039, &freeDeviceMemory); // CL_DEVICE_GLOBAL_FREE_MEMORY_AMD
freeDeviceMemory *= 1024;
cout << " Device reports " << freeDeviceMemory / (1024*1024) << "MByte free memory (AMD)" << endl;
deviceMemory = min<uint64_t>(deviceMemory, freeDeviceMemory);
}
if ((deviceMemory > needed_4G) && (!force3G)) {
cout << " Memory check for 4G kernel passed" << endl;
loadAndCompileKernel(nDev[di], pl, false);
} else if (deviceMemory > needed_3G) {
cout << " Memory check for 3G kernel passed" << endl;
loadAndCompileKernel(nDev[di], pl, true);
} else {
cout << " Memory check failed, required minimum memory: " << needed_3G/(1024*1024) << endl;
}
} else {
cout << " Device will not be used, it was not included in --devices parameter." << endl;
}
curDiv++;
}
}
if (devices.size() == 0) {
cout << "No compatible OpenCL devices found or all are deselected. Closing beamMiner." << endl;
exit(0);
}
}
// Setup function called from outside
void clHost::setup(beamStratum* stratumIn, vector<int32_t> devSel, bool allowCPU, bool force3G) {
stratum = stratumIn;
detectPlatFormDevices(devSel, allowCPU, force3G);
}
// Function that will catch new work from the stratum interface and then queue the work on the device
void clHost::queueKernels(uint32_t gpuIndex, clCallbackData* workData) {
cl_ulong4 work;
cl_ulong nonce;
// Get a new set of work from the stratum interface
stratum->getWork(workData->wd, (uint8_t *) &work);
nonce = workData->wd.nonce;
if (!is3G[gpuIndex]) { // Starting the 4G kernels
// Kernel arguments for cleanCounter
kernels[gpuIndex][0].setArg(0, buffers[gpuIndex][5]);
kernels[gpuIndex][0].setArg(1, buffers[gpuIndex][6]);
// Kernel arguments for round0
kernels[gpuIndex][1].setArg(0, buffers[gpuIndex][0]);
kernels[gpuIndex][1].setArg(1, buffers[gpuIndex][2]);
kernels[gpuIndex][1].setArg(2, buffers[gpuIndex][5]);
kernels[gpuIndex][1].setArg(3, work);
kernels[gpuIndex][1].setArg(4, nonce);
// Kernel arguments for round1
kernels[gpuIndex][2].setArg(0, buffers[gpuIndex][0]);
kernels[gpuIndex][2].setArg(1, buffers[gpuIndex][2]);
kernels[gpuIndex][2].setArg(2, buffers[gpuIndex][1]);
kernels[gpuIndex][2].setArg(3, buffers[gpuIndex][3]); // Index tree will be stored here
kernels[gpuIndex][2].setArg(4, buffers[gpuIndex][5]);
// Kernel arguments for round2
kernels[gpuIndex][3].setArg(0, buffers[gpuIndex][1]);
kernels[gpuIndex][3].setArg(1, buffers[gpuIndex][0]); // Index tree will be stored here
kernels[gpuIndex][3].setArg(2, buffers[gpuIndex][5]);
// Kernel arguments for round3
kernels[gpuIndex][4].setArg(0, buffers[gpuIndex][0]);
kernels[gpuIndex][4].setArg(1, buffers[gpuIndex][1]); // Index tree will be stored here
kernels[gpuIndex][4].setArg(2, buffers[gpuIndex][5]);
// Kernel arguments for round4
kernels[gpuIndex][5].setArg(0, buffers[gpuIndex][1]);
kernels[gpuIndex][5].setArg(1, buffers[gpuIndex][2]); // Index tree will be stored here
kernels[gpuIndex][5].setArg(2, buffers[gpuIndex][5]);
// Kernel arguments for round5
kernels[gpuIndex][6].setArg(0, buffers[gpuIndex][2]);
kernels[gpuIndex][6].setArg(1, buffers[gpuIndex][4]); // Index tree will be stored here
kernels[gpuIndex][6].setArg(2, buffers[gpuIndex][5]);
// Kernel arguments for Combine
kernels[gpuIndex][7].setArg(0, buffers[gpuIndex][0]);
kernels[gpuIndex][7].setArg(1, buffers[gpuIndex][1]);
kernels[gpuIndex][7].setArg(2, buffers[gpuIndex][2]);
kernels[gpuIndex][7].setArg(3, buffers[gpuIndex][3]);
kernels[gpuIndex][7].setArg(4, buffers[gpuIndex][4]);
kernels[gpuIndex][7].setArg(5, buffers[gpuIndex][5]);
kernels[gpuIndex][7].setArg(6, buffers[gpuIndex][6]);
cl_int err;
// Queue the kernels
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][0], cl::NDRange(0), cl::NDRange(12288), cl::NDRange(256), NULL, NULL);
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][1], cl::NDRange(0), cl::NDRange(22369536), cl::NDRange(256), NULL, NULL);
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][2], cl::NDRange(0), cl::NDRange(16777216), cl::NDRange(256), NULL, NULL);
queues[gpuIndex].flush();
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][3], cl::NDRange(0), cl::NDRange(16777216), cl::NDRange(256), NULL, NULL);
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][4], cl::NDRange(0), cl::NDRange(16777216), cl::NDRange(256), NULL, NULL);
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][5], cl::NDRange(0), cl::NDRange(16777216), cl::NDRange(256), NULL, NULL);
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][6], cl::NDRange(0), cl::NDRange(16777216), cl::NDRange(256), NULL, NULL);
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][7], cl::NDRange(0), cl::NDRange(4096), cl::NDRange(16), NULL, NULL);
} else { // Starting the 3G kernels
// Kernel arguments for cleanCounter
kernels[gpuIndex][0].setArg(0, buffers[gpuIndex][5]);
kernels[gpuIndex][0].setArg(1, buffers[gpuIndex][6]);
// Kernel arguments for round0
kernels[gpuIndex][1].setArg(0, buffers[gpuIndex][0]);
kernels[gpuIndex][1].setArg(1, buffers[gpuIndex][5]);
kernels[gpuIndex][1].setArg(2, work);
kernels[gpuIndex][1].setArg(3, nonce);
kernels[gpuIndex][1].setArg(4, (cl_uint) 0);
// Kernel arguments for round1
kernels[gpuIndex][2].setArg(0, buffers[gpuIndex][0]);
kernels[gpuIndex][2].setArg(1, buffers[gpuIndex][1]);
kernels[gpuIndex][2].setArg(2, buffers[gpuIndex][2]); // Index tree will be stored here
kernels[gpuIndex][2].setArg(3, buffers[gpuIndex][5]);
kernels[gpuIndex][2].setArg(4, (cl_uint) 0);
// Kernel arguments for round2
kernels[gpuIndex][3].setArg(0, buffers[gpuIndex][1]);
kernels[gpuIndex][3].setArg(1, buffers[gpuIndex][0]); // Index tree will be stored here
kernels[gpuIndex][3].setArg(2, buffers[gpuIndex][5]);
// Kernel arguments for move
kernels[gpuIndex][9].setArg(0, buffers[gpuIndex][2]);
kernels[gpuIndex][9].setArg(1, buffers[gpuIndex][1]);
// Kernel arguments for repack
kernels[gpuIndex][8].setArg(0, buffers[gpuIndex][1]);
kernels[gpuIndex][8].setArg(1, buffers[gpuIndex][0]);
kernels[gpuIndex][8].setArg(2, buffers[gpuIndex][2]); // Index tree will be stored here
// Kernel arguments for round3
kernels[gpuIndex][4].setArg(0, buffers[gpuIndex][0]);
kernels[gpuIndex][4].setArg(1, buffers[gpuIndex][1]); // Index tree will be stored here
kernels[gpuIndex][4].setArg(2, buffers[gpuIndex][5]);
// Kernel arguments for round4
kernels[gpuIndex][5].setArg(0, buffers[gpuIndex][1]);
kernels[gpuIndex][5].setArg(1, buffers[gpuIndex][0]); // Index tree will be stored here
kernels[gpuIndex][5].setArg(2, buffers[gpuIndex][5]);
// Kernel arguments for round5
kernels[gpuIndex][6].setArg(0, buffers[gpuIndex][0]);
kernels[gpuIndex][6].setArg(1, buffers[gpuIndex][4]); // Index tree will be stored here
kernels[gpuIndex][6].setArg(2, buffers[gpuIndex][5]);
// Kernel arguments for Combine
kernels[gpuIndex][7].setArg(0, buffers[gpuIndex][1]);
kernels[gpuIndex][7].setArg(1, buffers[gpuIndex][2]);
kernels[gpuIndex][7].setArg(2, buffers[gpuIndex][4]);
kernels[gpuIndex][7].setArg(3, buffers[gpuIndex][5]);
kernels[gpuIndex][7].setArg(4, buffers[gpuIndex][6]);
cl_int err;
// Queue the kernels
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][0], cl::NDRange(0), cl::NDRange(12288), cl::NDRange(256), NULL, NULL);
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][1], cl::NDRange(0), cl::NDRange(22369536), cl::NDRange(256), NULL, NULL);
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][2], cl::NDRange(0), cl::NDRange(8388608), cl::NDRange(256), NULL, NULL);
queues[gpuIndex].flush();
kernels[gpuIndex][1].setArg(4, (cl_uint) 1);
kernels[gpuIndex][2].setArg(4, (cl_uint) 1);
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][1], cl::NDRange(0), cl::NDRange(22369536), cl::NDRange(256), NULL, NULL);
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][2], cl::NDRange(0), cl::NDRange(8388608), cl::NDRange(256), NULL, NULL);
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][3], cl::NDRange(0), cl::NDRange(16777216), cl::NDRange(256), NULL, NULL);
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][9], cl::NDRange(0), cl::NDRange(34799616), cl::NDRange(256), NULL, NULL);
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][8], cl::NDRange(0), cl::NDRange(69599232), cl::NDRange(256), NULL, NULL);
queues[gpuIndex].flush();
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][4], cl::NDRange(0), cl::NDRange(16777216), cl::NDRange(256), NULL, NULL);
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][5], cl::NDRange(0), cl::NDRange(16777216), cl::NDRange(256), NULL, NULL);
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][6], cl::NDRange(0), cl::NDRange(16777216), cl::NDRange(256), NULL, NULL);
err = queues[gpuIndex].enqueueNDRangeKernel(kernels[gpuIndex][7], cl::NDRange(0), cl::NDRange(4096), cl::NDRange(16), NULL, NULL);
}
}
// this function will sumit the solutions done on GPU, then fetch new work and restart mining
void clHost::callbackFunc(cl_int err , void* data){
clCallbackData* workInfo = (clCallbackData*) data;
uint32_t gpu = workInfo->gpuIndex;
// Read the number of solutions of the last iteration
uint32_t solutions = results[gpu][0];
for (uint32_t i=0; i<solutions; i++) {
vector<uint32_t> indexes;
indexes.assign(32,0);
memcpy(indexes.data(), &results[gpu][4 + 32*i], sizeof(uint32_t) * 32);
stratum->handleSolution(workInfo->wd,indexes);
}
solutionCnt[gpu] += solutions;
// Get new work and resume working
if (stratum->hasWork()) {
queues[gpu].enqueueUnmapMemObject(buffers[gpu][6], results[gpu], NULL, NULL);
queueKernels(gpu, ¤tWork[gpu]);
results[gpu] = (unsigned *) queues[gpu].enqueueMapBuffer(buffers[gpu][6], CL_FALSE, CL_MAP_READ, 0, sizeof(cl_uint4) * 81, NULL, &events[gpu], NULL);
events[gpu].setCallback(CL_COMPLETE, &CCallbackFunc, (void*) ¤tWork[gpu]);
queues[gpu].flush();
} else {
paused[gpu] = true;
cout << "Device will be paused, waiting for new work" << endl;
}
}
void clHost::startMining() {
// Start mining initially
for (int i=0; i<devices.size(); i++) {
paused[i] = false;
currentWork[i].gpuIndex = i;
currentWork[i].host = (void*) this;
queueKernels(i, ¤tWork[i]);
results[i] = (unsigned *) queues[i].enqueueMapBuffer(buffers[i][6], CL_FALSE, CL_MAP_READ, 0, sizeof(cl_uint4) * 81, NULL, &events[i], NULL);
events[i].setCallback(CL_COMPLETE, &CCallbackFunc, (void*) ¤tWork[i]);
queues[i].flush();
}
// While the mining is running print some statistics
while (restart) {
this_thread::sleep_for(std::chrono::seconds(15));
// Print performance stats (roughly)
cout << "Performance: ";
uint32_t totalSols = 0;
for (int i=0; i<devices.size(); i++) {
uint32_t sol = solutionCnt[i];
solutionCnt[i] = 0;
totalSols += sol;
cout << fixed << setprecision(2) << (double) sol / 15.0 << " sol/s ";
}
if (devices.size() > 1) cout << "| Total: " << setprecision(2) << (double) totalSols / 15.0 << " sol/s ";
cout << endl;
// Check if there are paused devices and restart them
for (int i=0; i<devices.size(); i++) {
if (paused[i] && stratum->hasWork()) {
paused[i] = false;
// Same as above
queueKernels(i, ¤tWork[i]);
results[i] = (unsigned *) queues[i].enqueueMapBuffer(buffers[i][6], CL_FALSE, CL_MAP_READ, 0, sizeof(cl_uint4) * 81, NULL, &events[i], NULL);
events[i].setCallback(CL_COMPLETE, &CCallbackFunc, (void*) ¤tWork[i]);
queues[i].flush();
}
}
}
}
} // end namespace