Zobrazeno 1 - 10
of 261
pro vyhledávání: '"O'Boyle, Michael P."'
Autor:
Armengol-Estapé, Jordi, Rocha, Rodrigo C. O., Woodruff, Jackson, Minervini, Pasquale, O'Boyle, Michael F. P.
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. However, the development of thes
Externí odkaz:
http://arxiv.org/abs/2404.16041
Deep Neural Networks (DNNs) are extremely computationally demanding, which presents a large barrier to their deployment on resource-constrained devices. Since such devices are where many emerging deep learning applications lie (e.g., drones, vision-b
Externí odkaz:
http://arxiv.org/abs/2311.08909
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. Consequently, to avoid programs needin
Externí odkaz:
http://arxiv.org/abs/2310.04196
Autor:
Woodruff, Jackson, Koehler, Thomas, Brauckmann, Alexander, Cummins, Chris, Ainsworth, Sam, O'Boyle, Michael F. P.
Coarse-grained reconfigurable arrays (CGRAs) are domain-specific devices promising both the flexibility of FPGAs and the performance of ASICs. However, with restricted domains comes a danger: designing chips that cannot accelerate enough current and
Externí odkaz:
http://arxiv.org/abs/2309.09112
This work outlines a time-domain numerical integration technique for linear hyperbolic partial differential equations sourced by distributions (Dirac $\delta$-functions and their derivatives). Such problems arise when studying binary black hole syste
Externí odkaz:
http://arxiv.org/abs/2308.02385
Decompilation is a well-studied area with numerous high-quality tools available. These are frequently used for security tasks and to port legacy code. However, they regularly generate difficult-to-read programs and require a large amount of engineeri
Externí odkaz:
http://arxiv.org/abs/2305.12520
Autor:
Martínez, Pablo Antonio, Woodruff, Jackson, Armengol-Estapé, Jordi, Bernabé, Gregorio, García, José Manuel, O'Boyle, Michael F. P.
Publikováno v:
In Proceedings of the 32nd ACM SIGPLAN International Conference on Compiler Construction (CC '23), February 25-26, 2023, Montr\'eal, QC, Canada
Dedicated tensor accelerators demonstrate the importance of linear algebra in modern applications. Such accelerators have the potential for impressive performance gains, but require programmers to rewrite code using vendor APIs - a barrier to wider s
Externí odkaz:
http://arxiv.org/abs/2301.11659
Autor:
O'Boyle, Michael F., Markakis, Charalampos, Da Silva, Lidia J. Gomes, Macedo, Rodrigo Panosso, Kroon, Juan A. Valiente
The scheduled launch of the LISA Mission in the next decade has called attention to the gravitational self-force problem. Despite an extensive body of theoretical work, long-time numerical computations of gravitational waves from extreme-mass-ratio-i
Externí odkaz:
http://arxiv.org/abs/2210.02550
Publikováno v:
Armengol-Estap\'e, J. and O'Boyle, M. Learning C to x86 translation: An experiment in neural compilation. In Advances in Programming Languages and Neurosymbolic Systems Workshop, 2021. URL \url{https://openreview.net/forum?id=444ug_EYXet}
Deep learning has had a significant impact on many fields. Recently, code-to-code neural models have been used in code translation, code refinement and decompilation. However, the question of whether these models can automate compilation has yet to b
Externí odkaz:
http://arxiv.org/abs/2108.07639
Improving the performance of deep neural networks (DNNs) is important to both the compiler and neural architecture search (NAS) communities. Compilers apply program transformations in order to exploit hardware parallelism and memory hierarchy. Howeve
Externí odkaz:
http://arxiv.org/abs/2102.06599