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GPU code generation for ODE-based applications with phased shared-data access patterns
2013
ACM Transactions on Architecture and Code Optimization (TACO)
We present a novel code generation scheme for GPUs. Its key feature is the platform-aware generation of a heterogeneous pool of threads. This exposes more data-sharing opportunities among the concurrent threads and reduces the memory requirements that would otherwise exceed the capacity of the on-chip memory. Instead of the conventional strategy of focusing on exposing as much parallelism as possible, our scheme leverages on the phased nature of memory access patterns found in many applications
doi:10.1145/2555289.2555311
fatcat:5malqytdlrdtflqekx2d4ij2ji