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Auto-tuning has emerged as an important practical method for creating highly optimized code. However, the growing complexity of architectures and applications has resulted in a prohibitively large search space that preclude empirical auto-tuning. Here, we focus on the challenge to auto-tuning presented by applications that require auto-tuning of not just a small number of distinct kernels, but a large...
This article presents an optimized algorithm for Nonnegative Tensor Factorization (NTF), implemented in the CUDA (Compute Uniform Device Architecture) framework, that runs on contemporary graphics processors and exploits their massive parallelism. The NTF implementation is primarily targeted for analysis of high-dimensional spectral images, including dimensionality reduction, feature extraction, and...
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