Affiliation:
1. AICES, RWTH Aachen, Aachen, Germany
2. Intel Corporation
Abstract
We present Tensor Transpose Compiler (TTC), an open-source parallel compiler for multidimensional tensor transpositions. To generate high-performance C++ code, TTC explores a number of optimizations, including software prefetching, blocking, loop-reordering, and explicit vectorization. To evaluate the performance of multidimensional transpositions across a range of possible use-cases, we also release a benchmark covering arbitrary transpositions of up to six dimensions. Performance results show that the routines generated by TTC achieve close to peak memory bandwidth on both the Intel Haswell and the AMD Steamroller architectures and yield significant performance gains over modern compilers. By implementing a set of pruning heuristics, TTC allows users to limit the number of potential solutions; this option is especially useful when dealing with high-dimensional tensors, as the search space might become prohibitively large. Experiments indicate that when only 100 potential solutions are considered, the resulting performance is about 99% of that achieved with exhaustive search.
Funder
Deutsche Forschungsgemeinschaft
Publisher
Association for Computing Machinery (ACM)
Subject
Applied Mathematics,Software
Reference44 articles.
1. Martın Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg S. Corrado Andy Davis Jeffrey Dean Matthieu Devin etal 2015. TensorFlow: Large-scale machine learning on heterogeneous systems. Retrieved from https://www.tensorflow.org Martın Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg S. Corrado Andy Davis Jeffrey Dean Matthieu Devin et al. 2015. TensorFlow: Large-scale machine learning on heterogeneous systems. Retrieved from https://www.tensorflow.org
2. Coupled-cluster theory in quantum chemistry
3. Synthesis of High-Performance Parallel Programs for a Class of ab Initio Quantum Chemistry Models
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