David Gregg
Academic
Professor David Gregg is an associate professor of computer science and Fellow of Trinity College Dublin. His research deals with software performance optimization, particularly for multicore and low-power embedded systems. He has successfully commercialized outputs from his research, and he works closely with companies such as Movidius and IBM Research. He currently serves as Head of Software Systems within Trinity College.
.
2018. Optimal DNN Primitive Selection with Partitioned Boolean Quadratic Programming. Proceedings of the 2018 International Symposium on Code Generation and Optimization.
.
2017. Parallel Multi Channel convolution using General Matrix Multiplication. 2017 IEEE 28th International Conference on Application-specific Systems, Architectures and Processors (ASAP)2017 IEEE 28th International Conference on Application-specific Systems, Architectures and Processors (ASAP).
.
2017. Efficient Multibyte Floating Point Data Formats Using Vectorization. IEEE Transactions on Computers. 66:2081-2096.
.
2017. Low Complexity Multiply Accumulate Unit for Weight-Sharing Convolutional Neural Networks. IEEE Computer Architecture Letters. 16:132-135.
.
2017. Bitslice Vectors: A Software Approach to Customizable Data Precision on Processors with SIMD Extensions. 2017 46th International Conference on Parallel Processing (ICPP).
.
2016. Vectorization of Multibyte Floating Point Data Formats. Proceedings of the 2016 International Conference on Parallel Architectures and Compilation.
.
2016. Practical Algorithms for Finding Extremal Sets. J. Exp. Algorithmics. 21
.
2016. Practical Algorithms for Finding Extremal Sets. J. Exp. Algorithmics. 21
.
2016. Parallel Performance Problems on Shared-Memory Multicore Systems: Taxonomy and Observation. IEEE Transactions on Software Engineering. PP
.
2016. Low Complexity Multiply Accumulate Unit for Weight-Sharing Convolutional Neural Networks. IEEE Computer Architecture Letters. PP
Pages
- ‹ previous
- 1
- 2
- 3
- 4
- next ›
