Transforming the Hybrid Cloud for Emerging AI Workloads

no code implementations • 20 Nov 2024 • Deming Chen, Alaa Youssef, Ruchi Pendse, André Schleife, Bryan K. Clark, Hendrik Hamann, Jingrui He, Teodoro Laino, Lav Varshney, YuXiong Wang, Avirup Sil, Reyhaneh Jabbarvand, Tianyin Xu, Volodymyr Kindratenko, Carlos Costa, Sarita Adve, Charith Mendis, Minjia Zhang, Santiago Núñez-Corrales, Raghu Ganti, Mudhakar Srivatsa, Nam Sung Kim, Josep Torrellas, Jian Huang, Seetharami Seelam, Klara Nahrstedt, Tarek Abdelzaher, Tamar Eilam, Huimin Zhao, Matteo Manica, Ravishankar Iyer, Martin Hirzel, Vikram Adve, Darko Marinov, Hubertus Franke, Hanghang Tong, Elizabeth Ainsworth, Han Zhao, Deepak Vasisht, Minh Do, Fabio Oliveira, Giovanni Pacifici, Ruchir Puri, Priya Nagpurkar

This white paper, developed through close collaboration between IBM Research and UIUC researchers within the IIDAI Institute, envisions transforming hybrid cloud systems to meet the growing complexity of AI workloads through innovative, full-stack co-design approaches, emphasizing usability, manageability, affordability, adaptability, efficiency, and scalability.

Model Optimization scientific discovery +1

Repository-Level Compositional Code Translation and Validation

1 code implementation • 31 Oct 2024 • Ali Reza Ibrahimzada, Kaiyao Ke, Mrigank Pawagi, Muhammad Salman Abid, Rangeet Pan, Saurabh Sinha, Reyhaneh Jabbarvand

Several rule-based transpilers have been designed to automate code translation between different pairs of PLs.

Code Translation Translation

CodeMind: A Framework to Challenge Large Language Models for Code Reasoning

1 code implementation • 15 Feb 2024 • Changshu Liu, Shizhuo Dylan Zhang, Ali Reza Ibrahimzada, Reyhaneh Jabbarvand

The first two evaluate models to predict the execution output of an arbitrary code or code the model could correctly synthesize.

WhiteFox: White-Box Compiler Fuzzing Empowered by Large Language Models

1 code implementation • 24 Oct 2023 • Chenyuan Yang, Yinlin Deng, Runyu Lu, Jiayi Yao, Jiawei Liu, Reyhaneh Jabbarvand, Lingming Zhang

To this end, we propose WhiteFox, the first white-box compiler fuzzer using LLMs with source-code information to test compiler optimization, with a spotlight on detecting deep logic bugs in the deep learning (DL) compilers.

Code Generation Compiler Optimization

Automated Bug Generation in the era of Large Language Models

no code implementations • 3 Oct 2023 • Ali Reza Ibrahimzada, Yang Chen, Ryan Rong, Reyhaneh Jabbarvand

From the classic software engineering point of view, a hard-to-repair bug differs from the correct code in multiple locations, making it hard to localize and repair.

Program Repair

LeTI: Learning to Generate from Textual Interactions

1 code implementation • 17 May 2023 • Xingyao Wang, Hao Peng, Reyhaneh Jabbarvand, Heng Ji

We explore LMs' potential to learn from textual interactions (LETI) that not only check their correctness with binary labels but also pinpoint and explain errors in their outputs through textual feedback.

Code Generation Event Argument Extraction +1

Perfect is the enemy of test oracle

1 code implementation • 3 Feb 2023 • Ali Reza Ibrahimzada, Yigit Varli, Dilara Tekinoglu, Reyhaneh Jabbarvand

This paper presents SEER, a learning-based approach that in the absence of test assertions or other types of oracle, can determine whether a unit test passes or fails on a given method under test (MUT).

software testing