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Scout: high-performance heterogeneous computing made simple

Conference ·

Researchers must often write their own simulation and analysis software. During this process they simultaneously confront both computational and scientific problems. Current strategies for aiding the generation of performance-oriented programs do not abstract the software development from the science. Furthermore, the problem is becoming increasingly complex and pressing with the continued development of many-core and heterogeneous (CPU-GPU) architectures. To acbieve high performance, scientists must expertly navigate both software and hardware. Co-design between computer scientists and research scientists can alleviate but not solve this problem. The science community requires better tools for developing, optimizing, and future-proofing codes, allowing scientists to focus on their research while still achieving high computational performance. Scout is a parallel programming language and extensible compiler framework targeting heterogeneous architectures. It provides the abstraction required to buffer scientists from the constantly-shifting details of hardware while still realizing higb-performance by encapsulating software and hardware optimization within a compiler framework.

Research Organization:
Los Alamos National Laboratory (LANL)
Sponsoring Organization:
DOE
DOE Contract Number:
AC52-06NA25396
OSTI ID:
1049967
Report Number(s):
LA-UR-11-00593; LA-UR-11-593
Country of Publication:
United States
Language:
English

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