TY - GEN
T1 - IRIS Reimagined
T2 - 2nd International Workshop on Asynchronous Many-Task Systems and Applications, WAMTA 2024
AU - Miniskar, Narasinga Rao
AU - Lee, Seyong
AU - Beau, Johnston
AU - Young, Aaron
AU - Monil, Mohammad Alaul Haque
AU - Valero-Lara, Pedro
AU - Vetter, Jeffrey S.
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - CUDA
KW - DMEM
KW - Heterogeneous Computing
KW - HIP
KW - IRIS
KW - Runtime System
KW - Task based programming
UR - http://www.scopus.com/inward/record.url?scp=85197223530&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-61763-8_5
DO - 10.1007/978-3-031-61763-8_5
M3 - Conference contribution
AN - SCOPUS:85197223530
SN - 9783031617621
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 46
EP - 58
BT - Asynchronous Many-Task Systems and Applications - 2nd International Workshop, WAMTA 2024, Proceedings
A2 - Diehl, Patrick
A2 - Schuchart, Joseph
A2 - Valero-Lara, Pedro
A2 - Bosilca, George
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 14 February 2024 through 16 February 2024
ER -