DSL's
From Modelado Foundation
Sonia requested that Saman Amarasinghe and Dan Quinlan initiate this page. For comments, please contact them. This page is still in development.
| X-Stack Project | Name of the DSL | 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 | |
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| D-TEC | Halide | 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. | |
| DTEC | Shared Memory DSL | http://rosecompiler.org | MPI HPC applications on many core nodes | Internal LLNL App | Uses C | ROSE IR | Share memory optimization for MPI processes on many core architectures | ROSE | Many core architectures with local shared memory | |||
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