3 papers
cs.PL2026
Splyce: SIMD Vectorization of Sparse Coiteration
Kabilan Mahathevan, Poorna Gunathilaka, Kirshanthan Sundararajah
Sparse tensor contractions are bottlenecked by sparse-sparse coiteration loops that resist standard loop vectorization. We present Splyce, an auto-vectorization framework in MLIR t…
cs.DC2026
A Preliminary Study on Simultaneous Coscheduling for Discrete GPU vs. Fused GPU
Poorna Gunathilaka, Nabayan Chaudhury, Kirshanthan Sundararajah +1
CPU-GPU coscheduling enables simultaneous execution of an application across both processing units, but its efficiency depends on workload partitioning and memory architecture. Thi…
cs.PL2026
nomp: A Framework for Building Domain Specific Compilers
Thilina Ratnayaka, Kaushik Kulkarni, Nipuna Fernando +8
The low-level GPU programming models (CUDA, HIP, OpenCL, etc.) provide detailed control of the data flow and execution plan of a program in order to extract close-to-metal performa…