1 code implementation • 14 Feb 2024 • Nadav Schneider, Niranjan Hasabnis, Vy A. Vo, Tal Kadosh, Neva Krien, Mihai Capotă, Guy Tamir, Ted Willke, Nesreen Ahmed, Yuval Pinter, Timothy Mattson, Gal Oren
This study first investigates the performance of state-of-the-art language models in generating MPI-based parallel programs.
1 code implementation • 26 Dec 2023 • Mariano Tepper, Ishwar Singh Bhati, Cecilia Aguerrebere, Mark Hildebrand, Ted Willke
In this work, we present LeanVec, a framework that combines linear dimensionality reduction with vector quantization to accelerate similarity search on high-dimensional vectors while maintaining accuracy.
2 code implementations • 20 Dec 2023 • Tal Kadosh, Niranjan Hasabnis, Vy A. Vo, Nadav Schneider, Neva Krien, Mihai Capota, Abdul Wasay, Nesreen Ahmed, Ted Willke, Guy Tamir, Yuval Pinter, Timothy Mattson, Gal Oren
Specifically, we start off with HPC as a domain and build an HPC-specific LM, named MonoCoder, that is orders of magnitude smaller than existing LMs but delivers similar, if not better performance, on non-HPC and HPC tasks.
2 code implementations • 18 Aug 2023 • Tal Kadosh, Niranjan Hasabnis, Vy A. Vo, Nadav Schneider, Neva Krien, Abdul Wasay, Nesreen Ahmed, Ted Willke, Guy Tamir, Yuval Pinter, Timothy Mattson, Gal Oren
With easier access to powerful compute resources, there is a growing trend in the field of AI for software development to develop larger and larger language models (LLMs) to address a variety of programming tasks.
1 code implementation • 7 Apr 2023 • Cecilia Aguerrebere, Ishwar Bhati, Mark Hildebrand, Mariano Tepper, Ted Willke
In this work, we present new techniques and systems for creating faster and smaller graph-based indices.
no code implementations • 13 May 2022 • Romain Cosentino, Anirvan Sengupta, Salman Avestimehr, Mahdi Soltanolkotabi, Antonio Ortega, Ted Willke, Mariano Tepper
When used for transfer learning, the projector is discarded since empirical results show that its representation generalizes more poorly than the encoder's.
no code implementations • 8 Jun 2020 • Mariano Tepper, Dipanjan Sengupta, Ted Willke
We compare POSH, Binary OSL, and SphericalHash to several state-of-the-art hashing methods and provide empirical results for the superiority of the proposed methods across a wide range of standard benchmarks and parameter settings.
1 code implementation • 20 Sep 2019 • Ameer Haj-Ali, Nesreen K. Ahmed, Ted Willke, Sophia Shao, Krste Asanovic, Ion Stoica
However, these models are unable to capture the data dependency, the computation graph, or the organization of instructions.
Distributed, Parallel, and Cluster Computing Performance Programming Languages
no code implementations • 4 Aug 2019 • Ameer Haj-Ali, Nesreen K. Ahmed, Ted Willke, Joseph Gonzalez, Krste Asanovic, Ion Stoica
We propose a set of essential metrics to guide future works in evaluating the efficacy of using deep reinforcement learning in system optimization.
no code implementations • 2 Nov 2018 • Guixiang Ma, Nesreen K. Ahmed, Ted Willke, Dipanjan Sengupta, Michael W. Cole, Nicholas B. Turk-Browne, Philip S. Yu
We propose an end-to-end similarity learning framework called Higher-order Siamese GCN for multi-subject fMRI data analysis.