Eventually, it hit end of life and became AOCL [2]. I've not tried it, but I'm sure it's fine. It's ok. I did some experiments with transformer networks using

Eventually, it hit end of life and became AOCL [2]. I've not tried it, but I'm sure it's fine. It's ok. I did some experiments with transformer networks using libtorch. The numbers on a Ryzen 3700X were (sentences per second, 4 threads): OpenBLAS: 83, BLIS: 69, AMD BLIS: 80, MKL: 119 On a Xeon Gold 6138: OpenBLAS: 88, BLIS: 52, AMD BLIS: 59, MKL: 128 OpenBLAS was faster than AMD BLIS. But MKL beats everyone else by a wide margin because it has a special batched GEMM operation. Not only do they have very optimized kernels, they actively participate in the various ecosystems (such as PyTorch) and provide specialized implementations. AMD is doing well with hardware, but it's surprising how much they drop the ball with ROCm and the CPU software ecosystem. (Of course, they are doing great work with open sourcing GPU drivers, AMDVLK, etc.)