Democratizing Domain-Specific Computing

While architecture-guided optimizations and automated program transformation make it much easier to achieve high-performance DSA designs from C/C programs, the software community has introduced various DSLs for better design productivity in certain application domains. One good example is Halide,32 a widely used image-processing DSL, which has the advantageous property of decoupling the algorithm specification from performance optimization (via scheduling statements). This is very useful for image-processing applications; writing image-processing algorithms while parallelizing execution and optimizing for data locality and performance is difficult and time-consuming due to the large number of processing stages and the complex data dependency. However, the plain version of Halide only supports CPUs and GPUs. There is no way to easily synthesize the vast number of Halide programs to DSAs on FPGAs.