IEEE Signal Processing Magazine · 2012 · 41 citations · 5 references
ComputingComputer EngineeringComputer ScienceComputer ArchitectureParallel AlgorithmsParallel ComputingGraphics Processing Unit ArchitectureGraphics Processing UnitsKernel ProgrammingParallel ArchitecturesParallel Computer ArchitectureParallel Computing SystemsCompilation For Parallel ArchitecturesGpu ArchitectureKernel OptimizationLdpc CodesLow-density Parity-check CodesMulticore ArchitecturesMulticore SystemsOpencl Programming
This article proposes to address, in a tutorial style, the benefits of using Open Computing Language [1] (OpenCL) as a quick way to allow programmers to express and exploit parallelism in signal processing algorithms, such as those used in error-correcting code systems. In particular, we will show how multiplatform kernels can be developed straightforwardly using OpenCL to perform computationally intensive low-density parity-check (LDPC) decoding, targeting them to run on a large set of worldwide disseminated multicore architectures, such as x86 general purpose multicore central processing units (CPUs) and graphics processing units (GPUs). Moreover, devices with different architectures can be orchestrated to cooperatively execute these signal processing applications programmed in OpenCL. Experimental evaluation of the parallel kernels programmed with the OpenCL framework shows that high-performance can be achieved for distinct parallel computing architectures with low programming effort.
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Low-density parity-check codes
Robert G. Gallager · IEEE Transactions on Information Theory · 1962 · 10.6K citations · Full text
Multicore software technologies
Hahn Kim, Robert Bond · IEEE Signal Processing Magazine · 2009 · 36 citations · Full text