Can anyone try my tool on a 2080ti? On a 2080S it gets around 1300MKeys/sec when using 24-bit DP.
I tried your tool (DP18) on a V100.
[2020-06-22.11:35:37] [Info] Verifying 40336 results
[2020-06-22.11:35:45] [Info] DP: 0 TP: 0 992.50 Mpt/s (75 iter/s)
[2020-06-22.11:35:48] [Info] Verifying 40362 results
[2020-06-22.11:35:55] [Info] DP: 0 TP: 0 991.18 Mpt/s (75 iter/s)
Kangaroo on a server too, configured in the same way, however, it is not clear how many kangaroo are running in parallel with your program and what grid setting is used.
SolveKeyGPU Thread GPU#0: creating kangaroos...
SolveKeyGPU Thread GPU#0: 2^21.32 kangaroos [11.2s]
[2000.07 MK/s][GPU 2000.07 MK/s][Count 2^37.48][01:52][Server OK]
It says exactly how many kangaroos are running in parallel, 58,395,776 in this example:
______ ______ __ ___ __ ___ ____ ____ ___
/ ____// ____/ / / / | / |/ // __ ) / __ \ / |
/ __/ / / / / / /| | / /|_/ // __ |/ / / // /| |
/ /___ / /___ / /___ / ___ | / / / // /_/ // /_/ // ___ |
/_____ / \____/ /_____//_/ |_|/_/ /_//_____//_____//_/ |_|
EC LAMBDA CLIENT
VERSION 1.1.1 ALPHA
[2020-06-22.16:26:33] [Info] Connecting to 127.0.0.1
[2020-06-22.16:26:34] [Info] Target public key:
[2020-06-22.16:26:34] [Info] X:F1367CC260779F7EA6C7E4B7258A4D31A4C41D6282C5200571CE10E748A4AADE
[2020-06-22.16:26:34] [Info] Y:0743F0CA057C7F39A9D9A20D4A93555B19F712920EEEF2F267466A2F3D08662E
[2020-06-22.16:26:34] [Info] Distinguisher: 24 bits
[2020-06-22.16:26:34] [Info] Sending results to server every 10 minutes
[2020-06-22.16:26:34] [Info] Initializing GeForce RTX 2080 SUPER
[2020-06-22.16:26:34] [Info] Compiling OpenCL kernels...
[2020-06-22.16:26:34] [Info] Initializing...
[2020-06-22.16:27:09] [Info] Generating 58,395,776 starting points (7184.1MB)
[2020-06-22.16:27:37] [Info] 10.0%
[2020-06-22.16:27:42] [Info] 20.0%
[2020-06-22.16:27:48] [Info] 30.0%
[2020-06-22.16:27:50] [Info] 40.0%
[2020-06-22.16:27:50] [Info] 50.0%
[2020-06-22.16:27:50] [Info] 60.0%
[2020-06-22.16:27:51] [Info] 70.0%
[2020-06-22.16:27:51] [Info] 80.0%
[2020-06-22.16:27:52] [Info] 90.0%
[2020-06-22.16:27:52] [Info] 100.0%
[2020-06-22.16:27:54] [Info] Refilling GPU cache (319.3MB)
[2020-06-22.16:27:54] [Info] 10.0%
[2020-06-22.16:27:54] [Info] 20.0%
[2020-06-22.16:27:55] [Info] 30.0%
[2020-06-22.16:27:55] [Info] 40.0%
[2020-06-22.16:27:55] [Info] 50.0%
[2020-06-22.16:27:55] [Info] 60.0%
[2020-06-22.16:27:55] [Info] 70.0%
[2020-06-22.16:27:55] [Info] 80.0%
[2020-06-22.16:27:55] [Info] 90.0%
[2020-06-22.16:27:55] [Info] 100.0%
[2020-06-22.16:27:55] [Info] Tuning started
[2020-06-22.16:27:55] [Info] Results collection thread started
[2020-06-22.16:28:05] [Info] DP: 0 TP: 0 587.62 Mpt/s (10 iter/s)
[2020-06-22.16:28:15] [Info] DP: 0 TP: 0 1212.69 Mpt/s (20 iter/s)
[2020-06-22.16:28:25] [Info] DP: 0 TP: 0 1170.13 Mpt/s (20 iter/s)
[2020-06-22.16:28:28] [Info] Tuning complete
[2020-06-22.16:28:35] [Info] DP: 0 TP: 0 1187.71 Mpt/s (20 iter/s)
[2020-06-22.16:28:40] [Info] Verifying 2785 results
[2020-06-22.16:28:45] [Info] DP: 0 TP: 0 1325.58 Mpt/s (22 iter/s)
[2020-06-22.16:28:55] [Info] DP: 0 TP: 0 1322.54 Mpt/s (22 iter/s)
[2020-06-22.16:29:05] [Info] DP: 0 TP: 0 1315.67 Mpt/s (22 iter/s)
It automatically finds the best grid size, so I do not know if it's useful to even display it.
Increasing --gpu-mem-usage increases performance. By default it's low to avoid timing out/crashing for people testing it on display GPUs.