AMD and Intel have now published a full technical specification for ACE — AI Compute Extensions — the most significant overhaul to x86 AI compute in the architecture's history, co-authored by eight ...

Sparse Matrix-Vector Multiplication (SpMV) is important in scientific and industrial applications and remains a well-known challenge for modern CPUs due to high ...

Transformations are the key to such codes, and they rely on math that predates computing as we know it by centuries. There are all kinds of neat transformations. My personal favorite is the Fourier ...

Tensordyne says logarithmic computing could reduce AI inference costs and power demands, offering an alternative to conventional chip designs.

Abstract: Large-scale matrix multiplication is a computational bottleneck in various applications including artificial intelligence and machine learning. Given the time complexity of O(n 3) for matrix ...