42 citations · 47 across the 6 of their papers we have counts for
6 papers
Comparing Llama-2 and GPT-3 LLMs for HPC kernels generation
Pedro Valero-Lara, Alexis Huante, Mustafa Al Lail +4
We evaluate the use of the open-source Llama-2 model for generating well-known, high-performance computing kernels (e.g., AXPY, GEMV, GEMM) on different parallel programming models…
Analyzing the Performance Portability of Tensor Decomposition
S. Isaac Geronimo Anderson, Keita Teranishi, Daniel M. Dunlavy +1
We employ pressure point analysis and roofline modeling to identify performance bottlenecks and determine an upper bound on the performance of the Canonical Polyadic Alternating Po…
Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation
William F. Godoy, Pedro Valero-Lara, Keita Teranishi +2
We evaluate AI-assisted generative capabilities on fundamental numerical kernels in high-performance computing (HPC), including AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG. We t…
Parameter Sensitivity Analysis of the SparTen High Performance Sparse Tensor Decomposition Software: Extended Analysis
Jeremy M. Myers, Daniel M. Dunlavy, Keita Teranishi +1
Tensor decomposition models play an increasingly important role in modern data science applications. One problem of particular interest is fitting a low-rank Canonical Polyadic (CP…
Resiliency in Numerical Algorithm Design for Extreme Scale Simulations
Emmanuel Agullo, Mirco Altenbernd, Hartwig Anzt +33
This work is based on the seminar titled ``Resiliency in Numerical Algorithm Design for Extreme Scale Simulations'' held March 1-6, 2020 at Schloss Dagstuhl, that was attended by a…
RedThreads: An Interface for Application-level Fault Detection/Correction through Adaptive Redundant Multithreading
Saurabh Hukerikar, Keita Teranishi, Pedro C. Diniz +1
In the presence of accelerated fault rates, which are projected to be the norm on future exascale systems, it will become increasingly difficult for high-performance computing (HPC…