5 papers · 1 filter
Compiler-Driven Approximation Tuning for Hyperdimensional Computing
Xavier Routh, Abdul Rafae Noor, Akash Kothari +4
As Moore's law reaches its physical and economic limits, domain-specific approaches are increasingly employed to accelerate machine learning workloads. Hyperdimensional Computing (…
Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs
Yifan Zhao, Egan Johnson, Prasanth Chatarasi +2
Operator fusion has become a key optimization for deep learning, which combines multiple deep learning operators to improve data reuse and reduce global memory transfers. However,…
Towards Formal Verification of LLM-Generated Code from Natural Language Prompts
Aaron Councilman, David Jiahao Fu, Aryan Gupta +4
In the past few years LLMs have emerged as a tool that can aid programmers by taking natural language descriptions and generating code based on it. However, the reliability of LLM…
HPVM-HDC: A Heterogeneous Programming System for Accelerating Hyperdimensional Computing
Russel Arbore, Xavier Routh, Abdul Rafae Noor +7
Hyperdimensional Computing (HDC), a technique inspired by cognitive models of computation, has been proposed as an efficient and robust alternative basis for machine learning. HDC…
Hercules: A Compiler for Productive Programming of Heterogeneous Systems
Russel Arbore, Aaron Councilman, Xavier Routh +3
Modern computing systems increasingly rely on composing heterogeneous devices to improve performance and efficiency. Programming these systems is often unproductive: algorithm impl…