By that time we will have a good number of MI300 hosts. AMD Strix Halo (and the Intel equivalent?) will be out for high memory jobs locally. Intel Falcon Shores and who knows will finally be coming out, and from the looks of it the software ecosystem will be at least a little more hardware agnostic.
Seems like if you want to catch the wave, it's really already here. Not sure what this thing can do, and hope to find out next year, but local AI is going to be a killer app.
Halo Strix's memory bus will be twice as wide, higher speed, and the GPU will be much bigger. It will be closer to a small GPU with a huge VRAM pool, rather than a dreadfully slow IGP.
How is that an abstraction? It sounds more like a representation.
(have worked extensively with tf / pytorch)
> XeGPU dialect models a subset of Xe GPU’s unique features focusing on GEMM performance. The operations include 2d load, dpas, atomic, scattered load, 1d load, named barrier, mfence, and compile-hint. These operations provide a minimum set to support high-performance MLIR GEMM implementation for a wide range of GEMM shapes. XeGPU dialect complements Arith, Math, Vector, and Memref dialects. This allows XeGPU based MLIR GEMM implementation fused with other operations lowered through existing MLIR dialects.
Accelerators already have a common middle layer.
https://discourse.llvm.org/t/rfc-introducing-llvm-project-of...
