id | period | title | author | discussions-to | company_name | category | focus_area | open_source | amount_requested | status |
---|---|---|---|---|---|---|---|---|---|---|
100 |
3 |
GPU-based vanity address generator for Algorand |
Marcin Zawiejski (@dragmz) |
N/A |
Tools |
Other |
true |
47474 |
Approved |
A tool for generating Algorand vanity addresses using GPU acceleration.
- Marcin Zawiejski (dragmz) - experienced professional developer
- Author of VSCode Extension for TEAL and WalletConnect v1 and v2 libraries for Go
- Build-A-Bull hackathon top 5 finalist in the gaming track (see CnC: Claim & Conquer)
- go-algorand contributor
- The tool will be provided as a command line utility for systems that can run Python 3.11+ and have OpenCL 3.0 capable NVIDIA GPU
- It can lookup for multiple prefixes at the same run, making the process more efficient compared to a single prefix search
- The prefixes to look for can be specified as a command line argument or a text file
- Licence: MIT or similar (commercial use allowed)
- Includes best-effort maintenance for at least 3 months from the date of the first release
- Delivery date: up to 3 months since signing the xGov funding contract
Allows the community to quickly and securely generate recognizable Algorand addresses for their projects or personal use.
An example run of the tool:
pyagg --prefix AAAA,BBBB --count 10 --benchmark
Output:
Looking for 10 keys with prefixes: AAAA, BBBB
BBBBX2WLU3IYSM6GEPWOPJCYV5C7ZB3PHFL5NY5YPKIHUJGSKHHCV3WX54,[mnemonic]
BBBBPT2OSCPPBOT7JARKGMXP5LPUM54BPTBJFIHREKTQAH276WJ26EKUYY,[mnemonic]
AAAAUOLIHXUVH4ZM5F2HSOBFWQJDEXGVYZGV5E7RZKO6FFTTT2DKPKNQ5E,[mnemonic]
AAAA4Z36WWZA4DIKZYRFOV762IJ7QANHULGXFZEB6MU5456AKH62MZAY3A,[mnemonic]
BBBBVCHQ7QTMUUFCJAPRJU5RYHNWJQCF2KTC2LQ7HGY6FBDEUL2NEINZE4,[mnemonic]
AAAADJE7TJJI22ED55KMORZ74C3MZM7Y4XDO4HIKHFDRV3G5DA5T7ZJUXI,[mnemonic]
AAAAOQMUYLWDIUFERRDYLDHAASRGEOCS3CJTYM35F3S77WFQICGSSHI5BE,[mnemonic]
BBBBH7EHEHLCZDRUXSBVLFBGESFGKCEEDCVYLEIWMUAGJBFW6WDDKZHO4Q,[mnemonic]
BBBB3BG6L2FNZFQ5E2RI3D6LNIIC2NPI7XU2MJGMBPDKI6TJWURMRPTJ5M,[mnemonic]
BBBBHE7RDUIFEQKQKGZD5KLHI3YBYXDWP42XWWYKQ6VA6A66JHEU57FN6I,[mnemonic]
--- Benchmark Result
Devices: NVIDIA GeForce GTX 950
Total: 2725957 keys, matching: 10, time: 8.52s, avg: 319962 keys/s
(the [mnemonic] above is the 25-word mnemonic phrase for the generated Algorand address but it's been redacted for security reasons)