24 citations · 77 across the 28 of their papers we have counts for
6 papers · 1 filter
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…
Iris: First-Class Multi-GPU Programming Experience in Triton
Muhammad Awad, Muhammad Osama, Brandon Potter
Multi-GPU programming traditionally requires developers to navigate complex trade-offs between performance and programmability. High-performance implementations typically rely on l…
HipKittens: Fast and Furious AMD Kernels
William Hu, Drew Wadsworth, Sean Siddens +6
AMD GPUs offer state-of-the-art compute and memory bandwidth; however, peak performance AMD kernels are written in raw assembly. To address the difficulty of mapping AI algorithms…
Eliminating Multi-GPU Performance Taxes: A Systems Approach to Efficient Distributed LLMs
Octavian Alexandru Trifan, Karthik Sangaiah, Muhammad Awad +5
As large language models (LLMs) continue to scale, their workloads increasingly rely on distributed execution across multiple GPUs. However, the conventional bulk synchronous paral…
Optimizing Attention on GPUs by Exploiting GPU Architectural NUMA Effects
Mansi Choudhary, Karthik Sangaiah, Sonali Singh +3
The rise of disaggregated AI GPUs has exposed a critical bottleneck in large-scale attention workloads: non-uniform memory access (NUMA). As multi-chiplet designs become the norm f…
ELMF4EggQ: Ensemble Learning with Multimodal Feature Fusion for Non-Destructive Egg Quality Assessment
Md Zahim Hassan, Md. Osama, Muhammad Ashad Kabir +2
Accurate, non-destructive assessment of egg quality is critical for ensuring food safety, maintaining product standards, and operational efficiency in commercial poultry production…