MIT researchers develop new programming language for multicore image processing
August 06, 2012 // Nick Flaherty
Researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a new programming language for multicore image processing algorithms called Halide.
In tests, the MIT researchers used Halide to rewrite several common image-processing algorithms whose performance had already been optimized by seasoned programmers. The Halide versions were typically about one-third as long but offered significant performance gains two-, three-, or even six-fold speedups. In one instance, the Halide program was actually longer than the original but the speedup was 70-fold.
However the developmentis currently separate to the OpenCL multicore programming specification.
Jonathan Ragan-Kelley, a graduate student in the Department of Electrical Engineering and Computer Science (EECS), and Andrew Adams, a CSAIL postdoc, led the development of Halide, and they've released the code online.
Halide doesn't spare the programmer from thinking about how to parallelize efficiently on particular machines, but it splits that problem off from the description of the image-processing algorithms. A Halide program has two sections: one for the algorithms, and one for the processing "schedule." The schedule can specify the size and shape of the image chunks that each core needs to process at each step in the pipeline, and it can specify data dependencies for instance, that steps being executed on particular cores will need access to the results of previous steps on different cores. Once the schedule is drawn up, however, Halide handles all the accounting automatically.All news
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