4 papers
LIMINAL: Exploring The Frontiers of LLM Decode Performance
Michael Davies, Neal Crago, Karthikeyan Sankaralingam +1
The rapid advancement of Large Language Models (LLMs) necessitates a deep understanding of their fundamental performance limits. This paper investigates the limits of LLM inference…
Privacy-Preserving Performance Profiling of In-The-Wild GPUs
Ian McDougall, Michael Davies, Rahul Chatterjee +2
GPUs are the dominant platform for many important applications today including deep learning, accelerated computing, and scientific simulation. However, as the complexity of both a…
Pedagogically Motivated and Composable Open-Source RISC-V Processors for Computer Science Education
Ian McDougall, Harish Batchu, Michael Davies +1
While most instruction set architectures (ISAs) are only available to use through the purchase of a restrictive commercial license, the RISC-V ISA presents a free and open-source a…
Kitsune: Enabling Dataflow Execution on GPUs
Michael Davies, Neal Crago, Karthikeyan Sankaralingam +1
State of art DL models are growing in size and complexity, with many modern models also increasing in heterogeneity of behavior. GPUs are still the dominant platform for DL applica…