This container is a CUDA enabled build of xmrig/xmrig. It tracks the head of the master branch at build time. I used the guidance provided in the XMRig Build documentation for Ubuntu to put this image together.
To minimize the complexity of pulling in the required dependencies and minimizing the size of the image, I use the nvidia/cuda:11-2.0-devel image to build the xmrig binary. In the second stage, I copy the build artifacts to a new image dependent on nvidia/cuda:11.2.0-runtime.
The final image size is ~2.18GB compared to ~4.59GB when using the nvidia development image.
The entrypoint for the final image is /opt/xmrig/xmrig.
This provides the ability to pass arguments at container execution time. For example:
$ docker run --rm --gpus all -it kriation/xmrig:latest \
-t 4 --randomx-1gb-pages --bench=1M --cuda
* ABOUT XMRig/6.8.0 gcc/9.3.0
* LIBS libuv/1.34.2 OpenSSL/1.1.1f hwloc/2.1.0
* HUGE PAGES supported
* 1GB PAGES supported
* CPU Intel(R) Core(TM) i5-4670K CPU @ 3.40GHz (1) 64-bit AES
L2:1.0 MB L3:6.0 MB 4C/4T NUMA:1
* MEMORY 7.4/31.3 GB (24%)
* DONATE 0%
* ASSEMBLY auto:intel
* POOL #1 benchmark algo auto
* COMMANDS hashrate, pause, resume, results, connection
* OPENCL disabled
* CUDA 11.2/11.2/6.5.0
* CUDA GPU #0 01:00.0 GeForce GTX 1660 SUPER 1830/7001 MHz smx:22 arch:75 mem:1572/5941 MB
bench start benchmark hashes 1M algo rx/0
cpu use argon2 implementation AVX2
randomx init dataset algo rx/0 (4 threads) seed 0000000000000000...
randomx allocated 3072 MB (2080+256) huge pages 100% 3/3 +JIT (142 ms)
randomx dataset ready (6438 ms)
cpu use profile * (4 threads) scratchpad 2048 KB
nvidia use profile rx (1 thread) scratchpad 2048 KB
| # | GPU | BUS ID | INTENSITY | THREADS | BLOCKS | BF | BS | MEMORY | NAME
| 0 | 0 | 01:00.0 | 736 | 32 | 23 | 0 | 0 | 1472 | GeForce GTX 1660 SUPER
cpu READY threads 4/4 (4) huge pages 100% 4/4 memory 8192 KB (3 ms)
nvidia READY threads 1/1 (602 ms)
nvidia #0 01:00.0 0W 0C
miner speed 10s/60s/15m 2275.4 n/a n/a H/s max 2277.7 H/s
bench 12.55% 125485/1000000 (60.019s)
| CPU # | AFFINITY | 10s H/s | 60s H/s | 15m H/s |
| 0 | -1 | 407.6 | 407.7 | n/a |
| 1 | -1 | 412.6 | 412.6 | n/a |
| 2 | -1 | 636.7 | 636.5 | n/a |
| 3 | -1 | 638.8 | 638.5 | n/a |
| - | - | 2095.8 | 2095.3 | n/a |
| CUDA # | AFFINITY | 10s H/s | 60s H/s | 15m H/s |
| 0 | -1 | 181.3 | 180.3 | n/a | #0 01:00.0 GeForce GTX 1660 SUPER
| - | - | 180.4 | 180.3 | n/a |
miner speed 10s/60s/15m 2276.2 2275.6 n/a H/s max 2277.7 H/s
bench 17.89% 178922/1000000 (85.759s)
signal Ctrl+C received, exiting
cpu stopped (1 ms)
nvidia stopped (376 ms)
The prerequisite to using this image is that the NVIDIA container toolkit is configured properly on the container host. The documentation from NVIDIA on setting the toolkit up is straightforward.
In addition, I highly recommend that Huge Pages, 1GB Pages, and Hardware prefetching be configured per the XMRig documentation. The difference in hashrate on my test rig was more than 30%.
Content type
Image
Digest
Size
1.2 GB
Last updated
almost 6 years ago
docker pull kriation/xmrig