By Peter J. L. Wallis
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Extra info for Ada Software Tools Interfaces: Workshop, Bath, July 13–15, 1983 Proceedings
CREST  is an optimizing and tuning framework for exploiting inter-thread locality by thread coarsening optimization. Compared with Gcompiler, CREST involves safety analysis in its optimizing process. However, CREST’s coarsening strategy only focuses on improving data locality thus cannot eﬀectively reduce redundant instructions for GPGPU programs. In this paper, we present a practical compiler framework that can better exploit data sharing and performs thread coarsening for reducing redundant instructions.
GLES generated kernels achieve better performance on both GPUs because it applied more proﬁtable coarsening dimensions and granularities on each GPU. MRI-GRID, MRI-Q and FT are three major kernels in IMPATIENT MRI Toolset [7,18], which is a CUDA implementation for iterative MR image reconstruction. The result shows that GLES optimized kernel is similar with manually optimized kernel because we apply similar optimizations. 46 Z. Lin et al. MRI-Q is used in 3D MRI reconstruction algorithm. Manually optimized kernel leverage constant cache for sharing an array, which achieves better performance than our method on GTX 680.
The Cray compiler could inline procedures with primitive data type arguments. T7: Add data clauses to parallel regions. Both compilers were able to automatically generate a CPU-GPU memory copy command to transfer data between CPU-GPU when the array size is known at compilation time. Otherwise, the programmer has to manually specify the array size in data clauses. T8: Use the independent clause. The programmer can enable compiler parallelization using the independent clause to inform the compiler that the following loop does not carry dependences across iterations.
Ada Software Tools Interfaces: Workshop, Bath, July 13–15, 1983 Proceedings by Peter J. L. Wallis