IRIS Reimagined: Advancements in Intelligent Runtime System for Task-Based Programming

Conference · Wed May 01 04:00:00 EDT 2024

DOI:https://doi.org/10.1007/978-3-031-61763-8_5· OSTI ID:2438743

Miniskar, Narasinga Rao ^[1]; Lee, Seyong ^[1]; Johnston, Beau ^[1]; Young, Aaron ^[1]; Monil, M. A. H. ^[1]; Valero Lara, Pedro ^[1]; Vetter, Jeffrey ^[1]

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1. ORNL

Task-based programming models are gaining traction in scientific computing. IRIS is a portable runtime system that exploits multiple heterogeneous programming systems and can discover available resources and manage multiple diverse programming systems (e.g., CUDA, Hexagon, HIP, Level Zero, OpenCL, and OpenMP) simultaneously. It accounts for the constraints of task dependencies and provides customizable scheduling policies to map those tasks to heterogeneous devices. In this paper, we present new capabilities added to IRIS to improve its portability for heterogeneous programming, build-friendliness, and performance efficiency. The new additions include vendor-specific kernel support, a runtime system with a foreign function interface to eliminate writing wrapper or boilerplate code for heterogeneous kernels, an easy-to-use and configurable CMake-based build environment, automatic and efficient data transfers and orchestration, and the Hunter and DAGGER toolchains to evaluate IRIS’s task scheduling algorithms.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 2438743
• Country of Publication: United States
• Language: English