A low-power high precision self-testing data acquisition system for a large seismic exploration grid

Kejariwal, M.; Johnston, J.; Hopkins, Thomas A.; Drakshapalli, P.

doi:10.1049/cp:20050142

Cited by 2 publications

(1 citation statement)

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“…There has been a lot of research on iteration spaces and iterators (e.g. [52] in the context of translation validation and [23] in the context of partitioning), that formalize complex traversals by abstract iterators. Programs with nested loops are admitted, however our tool always focuses on parallelizing one inner loop at a time.…”

Section: Programs and Loopsmentioning

confidence: 99%

Synthesis of divide and conquer parallelism for loops

FarzanAzadeh¹,

NicoletVictor²

2017

SIGPLAN Not.

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This paper focuses on automated synthesis of divide-andconquer parallelism, which is a common parallel programming skeleton supported by many cross-platform multithreaded libraries. The challenges of producing (manually or automatically) a correct divide-and-conquer parallel program from a given sequential code are two-fold: (1) assuming that individual worker threads execute a code identical to the sequential code, the programmer has to provide the extra code for dividing the tasks and combining the computation results, and (2) sometimes, the sequential code may not be usable as is, and may need to be modified by the programmer. We address both challenges in this paper. We present an automated synthesis technique for the case where no modifications to the sequential code are required, and we propose an algorithm for modifying the sequential code to make it suitable for parallelization when some modification is necessary. The paper presents theoretical results for when this modification is efficiently possible, and experimental evaluation of the technique and the quality of the produced parallel programs.

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Section: Programs and Loopsmentioning

confidence: 99%