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The blog post is about using an NVIDIA-specific tensor core API that they have built to get good performance. Modular has been pushing the notion that they are
by subharmonicon 1y ago
The blog post is about using an NVIDIA-specific tensor core API that they have built to get good performance.
Modular has been pushing the notion that they are building technology that allows writing HW-vendor neutral solutions so that users can break free of NVIDIA's hold on high performance kernels.
From their own writing:
> We want a unified, programmable system (one small binary!) that can scale across architectures from multiple vendors—while providing industry-leading performance on the most widely used GPUs (and CPUs).
- totalperspectiv 1y agoThey allow you to write a kernel for Nvidia, or AMD, that can take full advantage of the Hardware of either one, then throw a compile time if-statement in there to switch which kernel to use based on the hardware available. So, you can support either vendor with as-good-vendor-library performance. That’s not lock-in to me at least. It’s not as good as the compiler being able to just magically produce optimized kernels for arbitrary hardware though, fully agree there. But it’s a big step forward from Cuda/HIP.