no code implementations • 1 Apr 2024 • Jordi Armengol-Estapé, Rodrigo C. O. Rocha, Jackson Woodruff, Pasquale Minervini, Michael F. P. O'Boyle
The escalating demand to migrate legacy software across different Instruction Set Architectures (ISAs) has driven the development of assembly-to-assembly translators to map between their respective assembly languages.
no code implementations • 6 Oct 2023 • Alexander Brauckmann, Elizabeth Polgreen, Tobias Grosser, Michael F. P. O'Boyle
MLIR is an emerging compiler infrastructure for modern hardware, but existing programs cannot take advantage of MLIR's high-performance compilation if they are described in lower-level general purpose languages.
no code implementations • 21 May 2023 • Jordi Armengol-Estapé, Jackson Woodruff, Chris Cummins, Michael F. P. O'Boyle
SLaDe is up to 6 times more accurate than Ghidra, a state-of-the-art, industrial-strength decompiler and up to 4 times more accurate than the large language model ChatGPT and generates significantly more readable code than both.
1 code implementation • NeurIPS Workshop AIPLANS 2021 • Jordi Armengol-Estapé, Michael F. P. O'Boyle
Deep learning has had a significant impact on many fields.
no code implementations • 21 May 2020 • Yuan Wen, Andrew Anderson, Valentin Radu, Michael F. P. O'Boyle, David Gregg
We optimize the trade-off between execution time and memory consumption by: 1) attempting to minimize execution time across the whole network by selecting data layouts and primitive operations to implement each layer; and 2) allocating an appropriate workspace that reflects the upper bound of memory footprint per layer.
2 code implementations • 20 Aug 2018 • Sajad Saeedi, Bruno Bodin, Harry Wagstaff, Andy Nisbet, Luigi Nardi, John Mawer, Nicolas Melot, Oscar Palomar, Emanuele Vespa, Tom Spink, Cosmin Gorgovan, Andrew Webb, James Clarkson, Erik Tomusk, Thomas Debrunner, Kuba Kaszyk, Pablo Gonzalez-de-Aledo, Andrey Rodchenko, Graham Riley, Christos Kotselidis, Björn Franke, Michael F. P. O'Boyle, Andrew J. Davison, Paul H. J. Kelly, Mikel Luján, Steve Furber
Visual understanding of 3D environments in real-time, at low power, is a huge computational challenge.
3 code implementations • 8 Oct 2014 • Luigi Nardi, Bruno Bodin, M. Zeeshan Zia, John Mawer, Andy Nisbet, Paul H. J. Kelly, Andrew J. Davison, Mikel Luján, Michael F. P. O'Boyle, Graham Riley, Nigel Topham, Steve Furber
Real-time dense computer vision and SLAM offer great potential for a new level of scene modelling, tracking and real environmental interaction for many types of robot, but their high computational requirements mean that use on mass market embedded platforms is challenging.