3 papers
cs.AR2026
Fleet: Hierarchical Task-based Abstraction for Megakernels on Multi-Die GPUs
Sangeeta Chowdhary, Ryan Swann, Sean Siddens +7
Modern GPUs adopt chiplet-based designs with multiple private cache hierarchies, but current programming models (CUDA/HIP) expose a flat execution hierarchy that cannot express chi…
cs.DC2025
tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection
Ryan Swann, Muhammad Osama, Xiaohu Guo +8
We present tritonBLAS, a fast and deterministic analytical model that uses architectural parameters like the cache hierarchy, and relative code and data placement to generate perfo…
cs.DC2025
SwizzlePerf: Hardware-Aware LLMs for GPU Kernel Performance Optimization
Arya Tschand, Muhammad Awad, Ryan Swann +5
Large language models (LLMs) have shown progress in GPU kernel performance engineering using inefficient search-based methods that optimize around runtime. Any existing approach la…