1 citations · 2 across the 6 of their papers we have counts for
7 papers
Microbenchmark-Driven Analytical Performance Modeling Across Modern GPU Architectures
Aaron Jarmusch, Sunita Chandrasekaran
Rapidly evolving GPU architectures featuring complex memory hierarchies, matrix units, and varied precision formats continue to widen the gap between theoretical peaks and achievab…
Execution-Centric Characterization of FP8 Matrix Cores, Asynchronous Execution, and Structured Sparsity on AMD MI300A
Aaron Jarmusch, Connor Vitz, Sunita Chandrasekaran
The AMD MI300A APU integrates CDNA3 GPUs with high-bandwidth memory and advanced accelerator features: FP8 matrix cores, asynchronous compute engines (ACE), and 2:4 structured spar…
Microbenchmarking NVIDIA's Blackwell Architecture: An in-depth Architectural Analysis
Aaron Jarmusch, Sunita Chandrasekaran
As GPU architectures rapidly evolve to meet the growing demands of exascale computing and machine learning, the performance implications of architectural innovations remain poorly…
LLM4VV: Evaluating Cutting-Edge LLMs for Generation and Evaluation of Directive-Based Parallel Programming Model Compiler Tests
Zachariah Sollenberger, Rahul Patel, Saieda Ali Zada +1
The usage of Large Language Models (LLMs) for software and test development has continued to increase since LLMs were first introduced, but only recently have the expectations of L…
Dissecting the NVIDIA Blackwell Architecture with Microbenchmarks
Aaron Jarmusch, Nathan Graddon, Sunita Chandrasekaran
The rapid development in scientific research provides a need for more compute power, which is partly being solved by GPUs. This paper presents a microarchitectural analysis of the…
LLM4VV: Exploring LLM-as-a-Judge for Validation and Verification Testsuites
Zachariah Sollenberger, Jay Patel, Christian Munley +2
Large Language Models (LLM) are evolving and have significantly revolutionized the landscape of software development. If used well, they can significantly accelerate the software d…