Hello, evolutionary algorithms by themselves I am not sure and don't have enough experience with atm. In our particular context the key is the intermediate repr

Hello, evolutionary algorithms by themselves I am not sure and don't have enough experience with atm. In our particular context the key is the intermediate representation on which the evolution happens and the compiler behaviors it triggers. We are still far from competitive against highly tuned expert code in computation-bound regimes but we do see >50% shared memory BW peak usage in nvprof in multiple cases. This first iteration is aimed at addressing the immediate research productivity needs: no need to write hundreds of lines of framework integration and low-level kernels to get a reasonable CUDA performance. We think we are helping remove the first immediate bottleneck that are very frustrating in practice to ML researchers when their layer does not translate exactly in supported, optimized, vendor libraries.