Invention Grant
- Patent Title: General distributed reduction for data parallel computing
- Patent Title (中): 数据并行计算的通用分布式减少
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Application No.: US12406842Application Date: 2009-03-18
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Publication No.: US08239847B2Publication Date: 2012-08-07
- Inventor: Yuan Yu , Pradeep Kumar Gunda , Michael A Isard
- Applicant: Yuan Yu , Pradeep Kumar Gunda , Michael A Isard
- Applicant Address: US WA Redmond
- Assignee: Microsoft Corporation
- Current Assignee: Microsoft Corporation
- Current Assignee Address: US WA Redmond
- Agency: Vierra Magen Marcus & DeNiro LLP
- Main IPC: G06F9/45
- IPC: G06F9/45

Abstract:
General-purpose distributed data-parallel computing using high-level computing languages is described. Data parallel portions of a sequential program written in a high-level language are automatically translated into a distributed execution plan. Map and reduction computations are automatically added to the plan. Patterns in the sequential program can be automatically identified to trigger map and reduction processing. Direct invocation of map and reduction processing is also provided. One or more portions of the reduce computation are pushed to the map stage and dynamic aggregation is inserted when possible. The system automatically identifies opportunities for partial reductions and aggregation, but also provides a set of extensions in a high-level computing language for the generation and optimization of the distributed execution plan. The extensions include annotations to declare functions suitable for these optimizations.
Public/Granted literature
- US20100241828A1 General Distributed Reduction For Data Parallel Computing Public/Granted day:2010-09-23
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