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PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
VERSION:1.0
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DTSTART:20151116T143000Z
DTEND:20151116T180000Z
LOCATION:17A
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: High-performance software is stretched between three ‘tent poles’: high-performance, parallel implementation, asymptotically optimal algorithms, and often highly technical application domains.  This tension contributes considerably to making HPC software difficult to write and hard to maintain.=0A=0ABuilding abstractions and tools to help maintain separation of concerns through domain-specific mini-languages (‘DSLs’), code generators, and tools is a proven, though difficult, way to help manage the complexity. This tutorial presents a set of tools rooted in the Python language that help with all parts of this process: First, with the design and implementation of DSLs, second, with transformation and rewriting of DSLs into various intermediate representations, third, with the transformation of DSL code into high-performance parallel code on GPUs and heterogeneous architectures, and fourth, with the creation and management of a runtime system for such code.  The tutorial includes a brief introduction to Python for those unfamiliar, and it is centered around frequent, short, and interactive practice problems.
SUMMARY:From Description to Code Generation: Building High-Performance Tools in Python
PRIORITY:3
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