4 papers
SPLASH: Co-Designing Sparse Attention with High-Bandwidth Flash for Efficient Long-Context Inference
Aditya Anirudh Jonnalagadda, Agasthi Haputhanthri, Pranav Dangi +5
The key-value (KV) cache has become the dominant consumer of memory in large language model (LLM) serving systems as context lengths, concurrency, and request lifetimes grow. High-…
LLM-based Hardware Development with Hierarchical IRs and End-to-End Multi-Agent Workflow
Chenyang Yin, Agasthi Haputhanthri, Aditya Anirudh Jonnalagadda +7
Large language models (LLMs) are increasingly used in software development, but their use in complex hardware design remains limited. This gap stems from both the scarcity of publi…
An Energy-Efficient Approximate Posit Multiply-Divide Unit
Rishi Thotli, Aditya Anirudh Jonnalagadda, Rishabh Hulsurkar +4
In modern computing units, division operations are generally slower than other arithmetic operations and require more resources, such as area and power, than multiplication. To red…
Closing the Gap Between Float and Posit Hardware Efficiency
Aditya Anirudh Jonnalagadda, Rishi Thotli, John L. Gustafson
The b-posit, or bounded posit, is a variation of the posit format designed for high performance computing (HPC) and AI applications. Unlike traditional floating-point formats (floa…