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DSL's: Difference between revisions

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|DSL 1  
|DSL 1  
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|Halide
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|D-TEC
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|http://halide-lang.org
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|Image processing algorithms
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|Cloverleaf, miniGMG, boxlib
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|Uses C++
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|Custom IR
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|Stencil optimizations (fusion, blocking, parallelization, vectorization) Schedules can produce all levels of locality, parallelism and redundant computation. OpenTuner for automatic schedule generation.
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|LLVM
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|X86 multicores, Arm and GPU
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|Working system. Used by Google and Adobe.
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|Local laplacian filter: Adobe top engineer took 3 months and 1500 loc to get 10x over original. Halide in 1-day, 60 lines 20x faster. In addition 90x faster GPU code in the same day (Adobe did not even try GPUs).  Also, all the pictures taken by google glass is processed using a Halide pipeline.
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|''Associated X-Stack Project  
|''Associated X-Stack Project  

Revision as of 16:07, April 29, 2014

Sonia requested that Saman Amarasinghe and Dan Quinlan initiate this page. For comments, please contact them. This page is still in development.

DSLs Name of the DSL Associated X-Stack Project URL Target domain Miniapps supported Front-end technology used Internal representation used Key Optimizations performed Code generation technology used Processors computing models targeted Current status Summary of the best results
DSL 1 Halide D-TEC http://halide-lang.org Image processing algorithms Cloverleaf, miniGMG, boxlib Uses C++ Custom IR Stencil optimizations (fusion, blocking, parallelization, vectorization) Schedules can produce all levels of locality, parallelism and redundant computation. OpenTuner for automatic schedule generation. LLVM X86 multicores, Arm and GPU Working system. Used by Google and Adobe. Local laplacian filter: Adobe top engineer took 3 months and 1500 loc to get 10x over original. Halide in 1-day, 60 lines 20x faster. In addition 90x faster GPU code in the same day (Adobe did not even try GPUs). Also, all the pictures taken by google glass is processed using a Halide pipeline.
Associated X-Stack Project
URL
Target domain
Miniapps supported (EXPRESS) (TG) (DEGAS) (D-TEC) (DynAX) (X-TUNE) (GVR) (CORVETTE) N/A (PIPER)
Xstack projects involved (EXPRESS) (TG) (DEGAS) (D-TEC) (DynAX) (X-TUNE) (GVR) (CORVETTE) N/A (PIPER)
Internal representation used (EXPRESS) (TG) (DEGAS) (D-TEC) (DynAX) (X-TUNE) (GVR) (CORVETTE) N/A (PIPER)
Key Optimizations performed (EXPRESS) (TG) (DEGAS) (D-TEC) (DynAX) (X-TUNE) (GVR) (CORVETTE) N/A (PIPER)
Code generation technology used (EXPRESS) (TG) (DEGAS) (D-TEC) (DynAX) (X-TUNE) (GVR) (CORVETTE) N/A (PIPER)
Processors/computing models targeted (EXPRESS) (TG) (DEGAS) (D-TEC) (DynAX) (X-TUNE) (GVR) (CORVETTE) N/A (PIPER)
Current status (EXPRESS) (TG) (DEGAS) (D-TEC) (DynAX) (X-TUNE) (GVR) (CORVETTE) N/A (PIPER)
Summary of the best results (EXPRESS) (TG) (DEGAS) (D-TEC) (DynAX) (X-TUNE) (GVR) (CORVETTE) N/A (PIPER)