75 lines
2.7 KiB
C++
75 lines
2.7 KiB
C++
/* XMRig
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* Copyright 2010 Jeff Garzik <jgarzik@pobox.com>
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* Copyright 2012-2014 pooler <pooler@litecoinpool.org>
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* Copyright 2014 Lucas Jones <https://github.com/lucasjones>
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* Copyright 2014-2016 Wolf9466 <https://github.com/OhGodAPet>
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* Copyright 2016 Jay D Dee <jayddee246@gmail.com>
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* Copyright 2017-2018 XMR-Stak <https://github.com/fireice-uk>, <https://github.com/psychocrypt>
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* Copyright 2018-2024 SChernykh <https://github.com/SChernykh>
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* Copyright 2016-2024 XMRig <https://github.com/xmrig>, <support@xmrig.com>
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*
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* This program is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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#include "backend/cuda/runners/CudaRxRunner.h"
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#include "backend/cuda/CudaLaunchData.h"
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#include "backend/cuda/wrappers/CudaLib.h"
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#include "base/net/stratum/Job.h"
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#include "crypto/rx/Rx.h"
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#include "crypto/rx/RxDataset.h"
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xmrig::CudaRxRunner::CudaRxRunner(size_t index, const CudaLaunchData &data) :
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CudaBaseRunner(index, data),
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m_datasetHost(data.thread.datasetHost() > 0)
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{
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m_intensity = m_data.thread.threads() * m_data.thread.blocks();
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const size_t scratchpads_size = m_intensity * m_data.algorithm.l3();
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const size_t num_scratchpads = scratchpads_size / m_data.algorithm.l3();
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if (m_intensity > num_scratchpads) {
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m_intensity = num_scratchpads;
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}
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m_intensity -= m_intensity % 32;
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}
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bool xmrig::CudaRxRunner::run(uint32_t startNonce, uint32_t *rescount, uint32_t *resnonce)
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{
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return callWrapper(CudaLib::rxHash(m_ctx, startNonce, m_target, rescount, resnonce));
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}
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bool xmrig::CudaRxRunner::set(const Job &job, uint8_t *blob)
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{
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if (!m_datasetHost && (m_seed != job.seed())) {
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m_seed = job.seed();
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if (m_ready) {
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const auto *dataset = Rx::dataset(job, 0);
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callWrapper(CudaLib::rxUpdateDataset(m_ctx, dataset->raw(), dataset->size(false)));
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}
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}
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const bool rc = CudaBaseRunner::set(job, blob);
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if (!rc || m_ready) {
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return rc;
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}
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const auto *dataset = Rx::dataset(job, 0);
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m_ready = callWrapper(CudaLib::rxPrepare(m_ctx, dataset->raw(), dataset->size(false), m_datasetHost, m_intensity));
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return m_ready;
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}
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