This project is currently no longer maintained as of 2017-12-03. -Marc

SILENTARMY

Official site: https://github.com/mbevand/silentarmy

SILENTARMY is a free open source Zcash miner for Linux with multi-GPU and Stratum support. It is written in OpenCL and has been tested on AMD/Nvidia/Intel GPUs, Xeon Phi, and more.

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
[...]

Usage:

$ 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

Performance

Vendor	Type	Model	sol/s
AMD	GPU	R9 Nano	115
AMD	GPU	R9 390X	100
AMD	GPU	R9 390	95
AMD	GPU	RX 480 8GB	75
NVIDIA	GPU	GTX 1070	70

See TROUBLESHOOTING.md to resolve performance issues.

Note: the 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 silentarmy miner.

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

1. Download the AMDGPU-PRO Driver (as of 12 Dec 2016, the latest version is 16.50).

2. Extract it: $ tar xf amdgpu-pro-16.50-362463.tar.xz

3. Install (non-root, will use sudo access automatically): $ ./amdgpu-pro-install

4. Add yourself to the video group if not already a member: $ sudo gpasswd -a $(whoami) video

5. Reboot

6. Download the AMD APP SDK (as of 27 Oct 2016, the latest version is 3.0)

7. Extract it: $ tar xf AMD-APP-SDKInstaller-v3.0.130.136-GA-linux64.tar.bz2

8. Install system-wide by running as root (accept all the default options): $ sudo ./AMD-APP-SDK-v3.0.130.136-GA-linux64.sh

Ubuntu 14.04 / fglrx

1. 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)

2. Follow steps 5-8 above: reboot, install the AMD APP SDK...

Ubuntu 16.04 / Nvidia

1. Install the OpenCL development files and the latest driver: $ sudo apt-get install nvidia-opencl-dev nvidia-361

2. Either reboot, or load the kernel driver: $ sudo modprobe nvidia_361

Ubuntu 16.04 / Intel

1. Install the OpenCL headers and library: $ sudo apt-get install beignet-opencl-icd

2. 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

1. SILENTARMY requires Python 3.3 or later (needed to support the use of the yield from syntax). On Ubuntu/Debian systems: $ sudo apt-get install python3

2. Verify the Python version is 3.3 or later: $ python3 -V

Step 3: C compiler

1. A C compiler is needed to compile the SILENTARMY solver binary (sa-solver): $ 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:

$ make

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 silentarmy and sa-solver to the same directory.

Equihash solver

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.

Implementation details

The 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.

The 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 input.cl.

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 xor_and_store()
• 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 kernel_sols() (see likely_invalids.)
• 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 verify_sol().

Finally, SILENTARMY makes many optimization assumptions and currently only supports Equihash parameters 200,9.

Author

Marc Bevand -- http://zorinaq.com

Donations welcome: t1cVviFvgJinQ4w3C2m2CfRxgP5DnHYaoFC

Thanks

I would like to thank these persons for their contributions to SILENTARMY, in alphabetical order:

• eXtremal
• jramos
• kenshirothefist
• Kubuxu
• lhl
• nerdralph
• poiuty
• solardiz

License

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.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.