7 citations · 19 across the 6 of their papers we have counts for
6 papers
Mojo: MLIR-Based Performance-Portable HPC Science Kernels on GPUs for the Python Ecosystem
William F. Godoy, Tatiana Melnichenko, Pedro Valero-Lara +5
We explore the performance and portability of the novel Mojo language for scientific computing workloads on GPUs. As the first language based on the LLVM's Multi-Level Intermediate…
Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions
Keita Teranishi, Harshitha Menon, William F. Godoy +25
We discuss the challenges and propose research directions for using AI to revolutionize the development of high-performance computing (HPC) software. AI technologies, in particular…
Characterizing GPU Energy Usage in Exascale-Ready Portable Science Applications
William F. Godoy, Oscar Hernandez, Paul R. C. Kent +8
We characterize the GPU energy usage of two widely adopted exascale-ready applications representing two classes of particle and mesh solvers: (i) QMCPACK, a quantum Monte Carlo pac…
A cast of thousands: How the IDEAS Productivity project has advanced software productivity and sustainability
Lois Curfman McInnes, Michael Heroux, David E. Bernholdt +31
Computational and data-enabled science and engineering are revolutionizing advances throughout science and society, at all scales of computing. For example, teams in the U.S. DOE E…
Julia as a unifying end-to-end workflow language on the Frontier exascale system
William F. Godoy, Pedro Valero-Lara, Caira Anderson +4
We evaluate Julia as a single language and ecosystem paradigm powered by LLVM to develop workflow components for high-performance computing. We run a Gray-Scott, 2-variable diffusi…
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…