9 citations · 10 across the 7 of their papers we have counts for
Showing cs.DCShow all
2 papers · 1 filter
cs.DC2026
Xe-Forge: Multi-Stage LLM-Powered Kernel Optimization for Intel GPU
Marcin Spoczynski, Daniel Fleischer, Moshe Berchansky +5
Porting deep learning algorithms to new hardware accelerators requires developers to repeatedly apply the same low-level optimizations -- quantization, memory access coalescing, ti…
cs.DC2026
Space Filling Curves is All You Need: Communication-Avoiding Matrix Multiplication Made Simple
Evangelos Georganas, Alexander Heinecke, Pradeep Dubey
General Matrix Multiplication (GEMM) is the cornerstone of HPC workloads and Deep Learning. State-of-the-art (SOTA) vendor libraries tune tensor layouts, parallelization schemes an…