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Raven algo mo bench fix

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This commit is contained in:
MoneroOcean 2020-11-04 00:31:27 +00:00
parent 6e63e92349
commit e0ea3d704d
3 changed files with 14 additions and 7 deletions
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2
src/base/net/stratum/EthStratumClient.cpp
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@ -177,7 +177,7 @@ void xmrig::EthStratumClient::parseNotification(const char *method, const rapidj
Job job;
job.setId(arr[0].GetString());
auto algo = m_pool.algorithm();
auto algo = Algorithm(Algorithm::KAWPOW_RVN); //m_pool.algorithm();
if (!algo.isValid()) {
algo = m_pool.coin().algorithm();
}

2
src/base/net/stratum/Pool.h
View file

@ -146,7 +146,7 @@ private:
Algorithm m_algorithm;
Coin m_coin;
int m_keepAlive = 0;
Mode m_mode = MODE_POOL;
Mode m_mode = MODE_AUTO_ETH;
ProxyUrl m_proxy;
std::bitset<FLAG_MAX> m_flags = 0;
String m_fingerprint;

17
src/core/MoBenchmark.cpp
View file

@ -158,11 +158,17 @@ void MoBenchmark::start(const BenchAlgo bench_algo) {
// prepare test job for benchmark runs ("benchmark" client id is to make sure we can detect benchmark jobs)
Job& job = *m_bench_job[bench_algo];
job.setId(algo.shortName()); // need to set different id so that workers will see job change
// 99 here to trigger all future bench_algo versions for auto veriant detection based on block version
job.setBlob("9905A0DBD6BF05CF16E503F3A66F78007CBF34144332ECBFC22ED95C8700383B309ACE1923A0964B00000008BA939A62724C0D7581FCE5761E9D8A0E6A1C3F924FDD8493D1115649C05EB601");
job.setTarget("FFFFFFFFFFFFFF20"); // set difficulty to 8 cause onJobResult after every 8-th computed hash
job.setHeight(1000);
job.setSeedHash("0000000000000000000000000000000000000000000000000000000000000001");
if (bench_algo == KAWPOW_RVN) {
job.setBlob("4c38e8a5f7b2944d1e4274635d828519b97bc64a1f1c7896ecdbb139988aa0e80000000000000000000000000000000000000000000000000000000000000000000000000000000000000000");
job.setDiff(Job::toDiff(strtoull("000000639c000000", nullptr, 16)));
job.setHeight(1500000);
} else {
// 99 here to trigger all future bench_algo versions for auto veriant detection based on block version
job.setBlob("9905A0DBD6BF05CF16E503F3A66F78007CBF34144332ECBFC22ED95C8700383B309ACE1923A0964B00000008BA939A62724C0D7581FCE5761E9D8A0E6A1C3F924FDD8493D1115649C05EB601");
job.setTarget("FFFFFFFFFFFFFF20"); // set difficulty to 8 cause onJobResult after every 8-th computed hash
job.setHeight(1000);
job.setSeedHash("0000000000000000000000000000000000000000000000000000000000000001");
}
m_bench_algo = bench_algo; // current perf bench_algo
m_hash_count = 0; // number of hashes calculated for current perf bench_algo
m_time_start = 0; // init time of the first result (in ms) during the first onJobResult
@ -214,6 +220,7 @@ void MoBenchmark::onJobResult(const JobResult& result) {
if (!(hashrate = t[1]))
if (!(hashrate = t[0]))
hashrate = static_cast<double>(m_hash_count) * result.diff / (now - m_bench_start) * 1000.0f;
if (m_bench_algo == KAWPOW_RVN) hashrate /= ((double)0xFFFFFFFFFFFFFFFF) / 0xFF000000;
m_bench_algo_perf[m_bench_algo] = hashrate; // store hashrate result
LOG_INFO("%s " BRIGHT_BLACK_BG(WHITE_BOLD_S " Algo " MAGENTA_BOLD_S "%s" WHITE_BOLD_S " hashrate: " CYAN_BOLD_S "%f "), Tags::benchmark(), Algorithm(ba2a[m_bench_algo]).shortName(), hashrate);
run_next_bench_algo(m_bench_algo);