This project is currently no longer maintained as of 2017-12-03. -Marc
Official site: https://github.com/mbevand/silentarmy
After compiling SILENTARMY, list the available OpenCL devices:
$ silentarmy --list
Start mining with two GPUs (ID 2 and ID 5) on a pool:
$ silentarmy --use 2,5 -c stratum+tcp://us1-zcash.flypool.org:3333 -u t1cVviFvgJinQ4w3C2m2CfRxgP5DnHYaoFC
When run without options, SILENTARMY mines with the first OpenCL device, using my donation address, on flypool:
$ silentarmy Connecting to us1-zcash.flypool.org:3333 Stratum server sent us the first job Mining on 1 device Total 0.0 sol/s [dev0 0.0] 0 shares Total 43.9 sol/s [dev0 43.9] 0 shares Total 46.9 sol/s [dev0 46.9] 0 shares Total 44.9 sol/s [dev0 44.9] 1 share [...]
$ silentarmy --help Usage: silentarmy [options] Options: -h, --help show this help message and exit -v, --verbose verbose mode (may be repeated for more verbosity) --debug enable debug mode (for developers only) --list list available OpenCL devices by ID (GPUs...) --use=LIST use specified GPU device IDs to mine, for example to use the first three: 0,1,2 (default: 0) --instances=N run N instances of Equihash per GPU (default: 2) -c POOL, --connect=POOL connect to POOL, for example stratum+tcp://example.com:1234 (add "#xnsub" to enable extranonce.subscribe) -u USER, --user=USER username for connecting to the pool -p PWD, --pwd=PWD password for connecting to the pool
|AMD||GPU||RX 480 8GB||75|
See TROUBLESHOOTING.md to resolve performance issues.
silentarmy miner automatically achieves this performance level, however the
sa-solver command-line solver by design runs only 1 instance of the Equihash proof-of-work algorithm causing it to slightly underperform by 5-10%. One must manually run 2 instances of
sa-solver (eg. in 2 terminal consoles) to achieve the same performance level as the
Compilation and installation
The steps below describe how to obtain the dependencies needed by SILENTARMY, how to compile it, and how to install it.
Step 1: OpenCL
OpenCL support comes with the graphic card driver. Read the appropriate subsection below:
Ubuntu 16.04 / amdgpu
Download the AMDGPU-PRO Driver (as of 12 Dec 2016, the latest version is 16.50).
$ tar xf amdgpu-pro-16.50-362463.tar.xz
Install (non-root, will use sudo access automatically):
Add yourself to the video group if not already a member:
$ sudo gpasswd -a $(whoami) video
Download the AMD APP SDK (as of 27 Oct 2016, the latest version is 3.0)
$ tar xf AMD-APP-SDKInstaller-v220.127.116.11-GA-linux64.tar.bz2
Install system-wide by running as root (accept all the default options):
$ sudo ./AMD-APP-SDK-v18.104.22.168-GA-linux64.sh
Ubuntu 14.04 / fglrx
Install the official Ubuntu package for the Radeon Software Crimson Edition driver:
$ sudo apt-get install fglrx(as of 30 Oct 2016, the latest version is 2:15.201-0ubuntu0.14.04.1)
Follow steps 5-8 above: reboot, install the AMD APP SDK...
Ubuntu 16.04 / Nvidia
Install the OpenCL development files and the latest driver:
$ sudo apt-get install nvidia-opencl-dev nvidia-361
Either reboot, or load the kernel driver:
$ sudo modprobe nvidia_361
Ubuntu 16.04 / Intel
Install the OpenCL headers and library:
$ sudo apt-get install beignet-opencl-icd
You must either alter the Makefile below or build silentarmy using
make OPENCL_HEADERS=/usr/lib/x86_64-linux-gnu/beignet/include/ LIBOPENCL=/usr/lib/x86_64-linux-gnu/beignet/ LDLIBS="-lcl -lrt"
Step 2: Python 3.3
SILENTARMY requires Python 3.3 or later (needed to support the use of the
yield fromsyntax). On Ubuntu/Debian systems:
$ sudo apt-get install python3
Verify the Python version is 3.3 or later:
$ python3 -V
Step 3: C compiler
- A C compiler is needed to compile the SILENTARMY solver binary (
$ sudo apt-get install build-essential
Step 4: Get SILENTARMY
Download it as a ZIP from github: https://github.com/mbevand/silentarmy/archive/master.zip
Or clone it from the command line:
$ git clone https://github.com/mbevand/silentarmy.git
Or, for Arch Linux users, get the silentarmy AUR package.
Step 5: Compile and install
Compiling SILENTARMY is easy:
You may need to specify the paths to the locations of your OpenCL C headers and libOpenCL.so if the compiler does not find them, eg.:
$ make OPENCL_HEADERS=/usr/local/cuda-8.0/targets/x86_64-linux/include LIBOPENCL=/usr/local/cuda-8.0/targets/x86_64-linux/lib
Self-testing the command-line solver (solves 100 all-zero 140-byte blocks with their nonces varying from 0 to 99):
$ make test
For more testing run
sa-solver --nonces 10000. It should finds 18627 solutions which is less than 1% off the theoretical expected average number of solutions of 1.88 per Equihash run at (n,k)=(200,9).
For installing, just copy
sa-solver to the same directory.
SILENTARMY also provides a command line Equihash solver (
sa-solver) implementing the CLI API described in the Zcash open source miner challenge. To solve a specific block header and print the encoded solution on stdout, run the following command (this header is from mainnet block #3400 and should result in 1 Equihash solution):
$ sa-solver -i 04000000e54c27544050668f272ec3b460e1cde745c6b21239a81dae637fde4704000000844bc0c55696ef9920eeda11c1eb41b0c2e7324b46cc2e7aa0c2aa7736448d7a000000000000000000000000000000000000000000000000000000000000000068241a587e7e061d250e000000000000010000000000000000000000000000000000000000000000
If the option
-i is not specified,
sa-solver solves a 140-byte header of all zero bytes. The option
--nonces <nr> instructs the program to try multiple nonces, each time incrementing the nonce by 1. So a convenient way to run a quick test/benchmark is simply:
$ sa-solver --nonces 100
Note: due to BLAKE2b optimizations in my implementation, if the header is specified it must be 140 bytes and its last 12 bytes must be zero.
Use the verbose (
-v) and very verbose (
-v -v) options to show the solutions and statistics in progressively more and more details.
silentarmy Python script is actually mostly a lightweight Stratum implementation which launches in the background one or more instances of
sa-solver --mining per GPU. This "mining mode" enables
sa-solver to communicate with
silentarmy using stdin/stdout. By default 2 instances of
sa-solver are launched for each GPU (this can be changed with the
silentarmy --instances N option.) 2 instances per GPU usually results in the best performance.
sa-solver binary invokes the OpenCL kernel which contains the core of the Equihash algorithm. My implementation uses two hash tables to avoid having to sort the (Xi,i) pairs:
- Round 0 (BLAKE2b) fills up table #0
- Round 1 reads table #0, identifies collisions, XORs the Xi's, stores the results in table #1
- Round 2 reads table #1 and fills up table #0 (reusing it)
- Round 3 reads table #0 and fills up table #1 (also reusing it)
- Round 8 (last round) reads table #1 and fills up table #0.
Only the non-zero parts of Xi are stored in the hash table, so fewer and fewer bytes are needed to store Xi as we progress toward round 8. For a description of the layout of the hash table, see the comment at the top of
Also the code implements the notion of "encoded reference to inputs" which I--apparently like most authors of Equihash solvers--independently discovered as a neat trick to save having to read/write so much data. Instead of saving lists of inputs that double in size every round, SILENTARMY re-uses the fact they were stored in the previous hash table, and saves a reference to the two previous inputs, encoded as a (row,slot0,slot1) where (row,slot0) and (row,slot1) themselves are each a reference to 2 previous inputs, and so on, until round 0 where the inputs are just the 21-bit values.
A BLAKE2b optimization implemented by SILENTARMY requires the last 12 bytes of the nonce/header to be zero. When set to a fixed value like zero, not only the code does not need to implement the "sigma" permutations, but many 64-bit additions in the BLAKE2b mix() function can be pre-computed automatically by the OpenCL compiler.
Managing invalid solutions (duplicate inputs) is done in multiple places:
- Any time a XOR results in an all-zero value, this work item is discarded as it is statistically very unlikely that the XOR of 256 or fewer inputs is zero. This check is implemented at the end of
- When the final hash table produced at round 8 has many elements that collide in the same row (because bits 160-179 are identical, and almost certainly bits 180-199), this is also discarded as a likely invalid solution because this is statistically guaranteed to be all inputs repeated at least once. This check is implemented in
- When input references are expanded on-GPU by
expand_refs(), the code checks if the last (512th) input is repeated at least once.
- Finally when the GPU returns potential solutions, the CPU also checks for invalid solutions with duplicate inputs. This check is implemented in
Finally, SILENTARMY makes many optimization assumptions and currently only supports Equihash parameters 200,9.
Marc Bevand -- http://zorinaq.com
Donations welcome: t1cVviFvgJinQ4w3C2m2CfRxgP5DnHYaoFC
I would like to thank these persons for their contributions to SILENTARMY, in alphabetical order:
The MIT License (MIT) Copyright (c) 2016 Marc Bevand
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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