192 lines
4.3 KiB
C++
192 lines
4.3 KiB
C++
/* XMRig
|
|
* Copyright (c) 2018-2020 SChernykh <https://github.com/SChernykh>
|
|
* Copyright (c) 2016-2020 XMRig <https://github.com/xmrig>, <support@xmrig.com>
|
|
*
|
|
* This program is free software: you can redistribute it and/or modify
|
|
* it under the terms of the GNU General Public License as published by
|
|
* the Free Software Foundation, either version 3 of the License, or
|
|
* (at your option) any later version.
|
|
*
|
|
* This program is distributed in the hope that it will be useful,
|
|
* but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
|
* GNU General Public License for more details.
|
|
*
|
|
* You should have received a copy of the GNU General Public License
|
|
* along with this program. If not, see <http://www.gnu.org/licenses/>.
|
|
*/
|
|
|
|
|
|
#include "backend/cuda/CudaWorker.h"
|
|
#include "backend/common/Tags.h"
|
|
#include "backend/cuda/runners/CudaCnRunner.h"
|
|
#include "backend/cuda/wrappers/CudaDevice.h"
|
|
#include "base/io/log/Log.h"
|
|
#include "base/tools/Alignment.h"
|
|
#include "base/tools/Chrono.h"
|
|
#include "core/Miner.h"
|
|
#include "crypto/common/Nonce.h"
|
|
#include "net/JobResults.h"
|
|
|
|
|
|
#ifdef XMRIG_ALGO_RANDOMX
|
|
# include "backend/cuda/runners/CudaRxRunner.h"
|
|
#endif
|
|
|
|
|
|
#ifdef XMRIG_ALGO_KAWPOW
|
|
# include "backend/cuda/runners/CudaKawPowRunner.h"
|
|
#endif
|
|
|
|
|
|
#include <cassert>
|
|
#include <thread>
|
|
|
|
|
|
namespace xmrig {
|
|
|
|
|
|
std::atomic<bool> CudaWorker::ready;
|
|
|
|
|
|
static inline bool isReady() { return !Nonce::isPaused() && CudaWorker::ready; }
|
|
|
|
|
|
} // namespace xmrig
|
|
|
|
|
|
|
|
xmrig::CudaWorker::CudaWorker(size_t id, const CudaLaunchData &data) :
|
|
GpuWorker(id, data.thread.affinity(), -1, data.device.index()),
|
|
m_algorithm(data.algorithm),
|
|
m_miner(data.miner)
|
|
{
|
|
switch (m_algorithm.family()) {
|
|
case Algorithm::RANDOM_X:
|
|
# ifdef XMRIG_ALGO_RANDOMX
|
|
m_runner = new CudaRxRunner(id, data);
|
|
# endif
|
|
break;
|
|
|
|
case Algorithm::ARGON2:
|
|
break;
|
|
|
|
case Algorithm::KAWPOW:
|
|
# ifdef XMRIG_ALGO_KAWPOW
|
|
m_runner = new CudaKawPowRunner(id, data);
|
|
# endif
|
|
break;
|
|
|
|
default:
|
|
m_runner = new CudaCnRunner(id, data);
|
|
break;
|
|
}
|
|
|
|
if (!m_runner) {
|
|
return;
|
|
}
|
|
|
|
if (!m_runner->init()) {
|
|
delete m_runner;
|
|
|
|
m_runner = nullptr;
|
|
}
|
|
}
|
|
|
|
|
|
xmrig::CudaWorker::~CudaWorker()
|
|
{
|
|
delete m_runner;
|
|
}
|
|
|
|
|
|
void xmrig::CudaWorker::jobEarlyNotification(const Job &job)
|
|
{
|
|
if (m_runner) {
|
|
m_runner->jobEarlyNotification(job);
|
|
}
|
|
}
|
|
|
|
|
|
bool xmrig::CudaWorker::selfTest()
|
|
{
|
|
return m_runner != nullptr;
|
|
}
|
|
|
|
|
|
size_t xmrig::CudaWorker::intensity() const
|
|
{
|
|
return m_runner ? m_runner->roundSize() : 0;
|
|
}
|
|
|
|
|
|
void xmrig::CudaWorker::start()
|
|
{
|
|
while (Nonce::sequence(Nonce::CUDA) > 0) {
|
|
if (!isReady()) {
|
|
do {
|
|
std::this_thread::sleep_for(std::chrono::milliseconds(200));
|
|
}
|
|
while (!isReady() && Nonce::sequence(Nonce::CUDA) > 0);
|
|
|
|
if (Nonce::sequence(Nonce::CUDA) == 0) {
|
|
break;
|
|
}
|
|
|
|
if (!consumeJob()) {
|
|
return;
|
|
}
|
|
}
|
|
|
|
while (!Nonce::isOutdated(Nonce::CUDA, m_job.sequence())) {
|
|
uint32_t foundNonce[16] = { 0 };
|
|
uint32_t foundCount = 0;
|
|
|
|
if (!m_runner->run(readUnaligned(m_job.nonce()), &foundCount, foundNonce)) {
|
|
return;
|
|
}
|
|
|
|
if (foundCount) {
|
|
JobResults::submit(m_job.currentJob(), foundNonce, foundCount, m_deviceIndex);
|
|
}
|
|
|
|
if (!Nonce::isOutdated(Nonce::CUDA, m_job.sequence()) && !m_job.nextRound(1, intensity())) {
|
|
JobResults::done(m_job.currentJob());
|
|
}
|
|
|
|
storeStats();
|
|
std::this_thread::yield();
|
|
}
|
|
|
|
if (!consumeJob()) {
|
|
return;
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
bool xmrig::CudaWorker::consumeJob()
|
|
{
|
|
if (Nonce::sequence(Nonce::CUDA) == 0) {
|
|
return false;
|
|
}
|
|
|
|
m_job.add(m_miner->job(), intensity(), Nonce::CUDA);
|
|
|
|
return m_runner->set(m_job.currentJob(), m_job.blob());
|
|
}
|
|
|
|
|
|
void xmrig::CudaWorker::storeStats()
|
|
{
|
|
if (!isReady()) {
|
|
return;
|
|
}
|
|
|
|
m_count += m_runner ? m_runner->processedHashes() : 0;
|
|
|
|
const uint64_t timeStamp = Chrono::steadyMSecs();
|
|
m_hashrateData.addDataPoint(m_count, timeStamp);
|
|
|
|
GpuWorker::storeStats();
|
|
}
|