For CUDA and CPU mining with your libraries, I added some of the benchmark files for mining photons to a repo here:
Some links in the c++ may be broken as I moved them from a top-level in another copy of the repo.
The above was made by ChatGPT pro, I have not run or verified it myself. I would NOT trust the BCH Secp256 implementation anywhere outside the current application, where it seems to work quite well.
Your issue seems to give a straight-forward proposal for exploring the topic.
@shrec Thanks for publishing this work it helped me in building a high-performance optimized GPU miner for Cashtokens
you using my engin on backend or based my codes you build your code separatly ? if my engin is used i will add your project in adoptions
Thanks, @ABLA. I’m glad UltrafastSecp256k1 helped you build Pickaxe, and I appreciate the work you’ve put into the miner.
I’ve been optimizing a local version and am now seeing about 1.22 GH/s on my RTX5060ti GPU. I’d prefer to work together on bringing those improvements to Pickaxe. If you’re interested, let’s discuss the integration and a fair share of Pickaxe’s existing donation privately.
I integrated a Rust port of UltrafastSecp256k1 CPU and NVIDIA GPU arithmetic into Pickaxe and contributed it back through PR #444.
Tests ran on an NVIDIA RTX 50-series GPU with roughly desktop RTX 5070 Ti- Laptop class graphics performance:
| Implementation | Hash rate | Comparison |
|---|---|---|
| PHOTON reference associated with 2qx’s work | ~2 MH/s, estimated | Reference baseline |
| My legacy Pickaxe kernel | 114.24 MH/s | ~57× the estimated reference |
| Pickaxe with the UltrafastSecp256k1 Rust port | 123.17 MH/s | 7.82% above my legacy kernel |
The initial direct integration of UltrafastSecp256k1 produced a lower hash rate for Pickaxe’s workload. I therefore ported the required arithmetic into Rust while retaining Pickaxe’s specialized mining logic and optimizations.
Repeated tests on the same GPU showed 6.6–7.8% higher hash rate, with correctness checks passing. I selected this backend for the updated v0.0.1 and kept my legacy implementation available for reference.
