Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Baghdadi, Riyadh"'
Autor:
Bachiri, Inas, Benmeziane, Hadjer, Niar, Smail, Baghdadi, Riyadh, Ouarnoughi, Hamza, Aries, Abdelkrime
Deep Learning models have experienced exponential growth in complexity and resource demands in recent years. Accelerating these models for efficient execution on resource-constrained devices has become more crucial than ever. Two notable techniques e
Externí odkaz:
http://arxiv.org/abs/2408.04116
Code language models have emerged as useful tools for various programming tasks, yet they often struggle when it comes to complex ones. In this paper, we explore the potential of curriculum learning in enhancing the performance of these models. While
Externí odkaz:
http://arxiv.org/abs/2407.10194
Deep hashing techniques have emerged as the predominant approach for efficient image retrieval. Traditionally, these methods utilize pre-trained convolutional neural networks (CNNs) such as AlexNet and VGG-16 as feature extractors. However, the incre
Externí odkaz:
http://arxiv.org/abs/2403.13747
Autor:
Merouani, Massinissa, Boudaoud, Khaled Afif, Aouadj, Iheb Nassim, Tchoulak, Nassim, Bernou, Islem Kara, Benyamina, Hamza, Tayeb, Fatima Benbouzid-Si, Benatchba, Karima, Leather, Hugh, Baghdadi, Riyadh
While polyhedral compilers have shown success in implementing advanced code transformations, they still have challenges in selecting the most profitable transformations that lead to the best speedups. This has motivated the use of machine learning to
Externí odkaz:
http://arxiv.org/abs/2403.11522
In recent years, data has emerged as the new gold, serving as a powerful tool for creating intelligent systems. However, procuring high-quality data remains challenging, especially for code. To address this, we developed TinyPy Generator, a tool that
Externí odkaz:
http://arxiv.org/abs/2403.06503
Autor:
Ibrahim, Hazem, Liu, Fengyuan, Asim, Rohail, Battu, Balaraju, Benabderrahmane, Sidahmed, Alhafni, Bashar, Adnan, Wifag, Alhanai, Tuka, AlShebli, Bedoor, Baghdadi, Riyadh, Bélanger, Jocelyn J., Beretta, Elena, Celik, Kemal, Chaqfeh, Moumena, Daqaq, Mohammed F., Bernoussi, Zaynab El, Fougnie, Daryl, de Soto, Borja Garcia, Gandolfi, Alberto, Gyorgy, Andras, Habash, Nizar, Harris, J. Andrew, Kaufman, Aaron, Kirousis, Lefteris, Kocak, Korhan, Lee, Kangsan, Lee, Seungah S., Malik, Samreen, Maniatakos, Michail, Melcher, David, Mourad, Azzam, Park, Minsu, Rasras, Mahmoud, Reuben, Alicja, Zantout, Dania, Gleason, Nancy W., Makovi, Kinga, Rahwan, Talal, Zaki, Yasir
The emergence of large language models has led to the development of powerful tools such as ChatGPT that can produce text indistinguishable from human-generated work. With the increasing accessibility of such technology, students across the globe may
Externí odkaz:
http://arxiv.org/abs/2305.13934
Autor:
Merouani, Massinissa, Boudaoud, Khaled Afif, Aouadj, Iheb Nassim, Tchoulak, Nassim, Benbouzid-Sitayeb, Fatima, Benatchba, Karima, Leather, Hugh, Baghdadi, Riyadh
Publikováno v:
In Proceedings of 12th International Workshop on Polyhedral Compilation Techniques (IMPACT 2022)
In this paper, we present a work in progress about a deep learning based approach for automatic code optimization in polyhedral compilers. The proposed technique explores combinations of affine and non-affine loop transformations to find the sequence
Externí odkaz:
http://arxiv.org/abs/2206.03684
Autor:
Kourta, Smail, Namani, Adel, Tayeb, Fatima Benbouzid-Si, Hazelwood, Kim, Cummins, Chris, Leather, Hugh, Baghdadi, Riyadh
Term Rewriting Systems (TRSs) are used in compilers to simplify and prove expressions. State-of-the-art TRSs in compilers use a greedy algorithm that applies a set of rewriting rules in a predefined order (where some of the rules are not axiomatic).
Externí odkaz:
http://arxiv.org/abs/2111.12116
Autor:
Amarasinghe, Saman, Baghdadi, Riyadh, Davoudi, Zohreh, Detmold, William, Illa, Marc, Parreno, Assumpta, Pochinsky, Andrew V., Shanahan, Phiala E., Wagman, Michael L.
Publikováno v:
Phys. Rev. D 107, 094508 (2023)
The low-energy spectrum and scattering of two-nucleon systems are studied with lattice quantum chromodynamics using a variational approach. A wide range of interpolating operators are used: dibaryon operators built from products of plane-wave nucleon
Externí odkaz:
http://arxiv.org/abs/2108.10835
Autor:
Baghdadi, Riyadh, Merouani, Massinissa, Leghettas, Mohamed-Hicham, Abdous, Kamel, Arbaoui, Taha, Benatchba, Karima, Amarasinghe, Saman
Publikováno v:
Proceedings of the 4th MLSys Conference, San Jose, CA, USA, 2021
Enabling compilers to automatically optimize code has been a longstanding goal for the compiler community. Efficiently solving this problem requires using precise cost models. These models predict whether applying a sequence of code transformations r
Externí odkaz:
http://arxiv.org/abs/2104.04955