The wgsl implementation is called from fp_all.wgsl
cd bls12_381cargo test
cd bls12_381cargo bench
| Parameter | Value |
|---|---|
| name | "Apple M1 GPU" |
| vendor | "Apple Inc." |
| device | "M1" |
| device_type | "IntegratedGpu" |
| driver | "Apple" |
| driver_info | "Metal" |
| backend | "Metal" |
The time cell that contains N/A are either not implemented yet, for that column
| Function | GPU Time | CPU Time |
|---|---|---|
| Bigint multiply | 78.777 ms - 80.046 ms | N/A |
| Bigint add | 83.114 ms - 87.527 ms | N/A |
| Bigint adc | 82.748 ms - 91.893 ms | 0.0002 ps - 0.0003 ps |
| Bigint mac | 81.285 ms - 89.749 ms | 0.0001 ps - 0.0003 ps |
| Fp multiply | 79.876 ms - 87.774 ms | 15.271 ns - 15.339 ns |
| Fp subtract | 78.921 ms - 87.439 ms | 14.831 ns - 14.896 ns |
| Fp2 add | 78.539 ms - 85.524 ms | N/A |
| Fp6 add | 79.135 ms - 87.809 ms | N/A |
| G1projective Generator is on curve | 81.086 ms - 90.459 ms | 190.36 ns - 206.23 ns |
| G1Projective identity is on curve | 84.144 ms - 93.578 ms | 192.16 ns - 202.12 ns |
| G1Projective test equality | 80.747 ms - 88.283 ms | N/A |
| G1projective test conditionally select affine | 92.884 ms - 101.86 ms | 55.251 ns - 55.481 ns |
| full pairing | N/A | 1.4428 ms - 1.5749 ms |
| G2 preparation for pairing | N/A | 159.91 µs - 168.94 µs |
| miller loop for pairing | N/A | 400.06 µs - 418.87 µs |
| final exponentiation for pairing | N/A | 894.33 µs - 930.23 µs |
| G1Affine scalar multiplication | N/A | 374.31 µs - 379.78 µs |
| G1Affine subgroup check | N/A | 79.742 µs - 81.061 µs |
| G1Affine deserialize compressed point | N/A | 113.59 µs - 126.59 µs |
| G1Affine deserialize uncompressed point | N/A | 80.260 µs - 81.992 µs |
The huge time discrepancy in the GPU side is because
- The time is actually sum of time required to initialize wgpu, run compute shaders, pass the data to CPU.
let c = pollster::block_on(run(&vec![9, 4], "multiply_test"));
- further optimization is needed which includes selecting appropriate workgroup sizes
Accurate time reading will be done, once the core functionalities are implemented.