The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Poster Type: Research Posters
Author: Narasinga Rao Miniskar (Oak Ridge National Laboratory (ORNL)), Pedro Valero-Lara (Oak Ridge National Laboratory (ORNL)), William Godoy (Oak Ridge National Laboratory (ORNL)), Keita Teranishi (Oak Ridge National Laboratory (ORNL)), Jeffrey S. Vetter (Oak Ridge National Laboratory (ORNL))
Supervisor:
Abstract: Julia, a high-performance, high-level language, harnesses dynamic typing and LLVM’s Just-in-Time compiler to match the speed of C and Fortran in production. Meanwhile, IRIS serves as a heterogeneous runtime that discovers devices dynamically and schedules concurrent work on CPUs, GPUs, FPGAs, and DSPs today. Integrating Julia with IRIS unlocks high-performance, portable, and productive computing for workloads. This synergy simplifies kernel APIs for both data-parallel and task-parallel execution, and it also builds task graphs with intelligent flow-dependency detection via kernel analysis to optimize performance across multiple device types. We report early results of AXPY executing on CUDA GPUs today. A tiled heterogeneous math library for DGEMM uses vendor kernels, demonstrating the system’s versatility.
Best Poster Finalist (BP): no
Poster: PDF
Poster Summary: PDF