Update app.py

app.py

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 27 Jun 2023 | Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation | ⬇️
 William F. Godoy, Pedro Valero-Lara, Keita Teranishi, Prasanna Balaprakash, Jeffrey S. Vetter
 
-We evaluate AI-assisted generative capabilities on fundamental numerical kernels in high-performance computing (HPC), including AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG. We test the generated kernel codes for a variety of language-supported programming models, including (1) C++ (e.g., OpenMP [including offload], OpenACC, Kokkos, SyCL, CUDA, and HIP), (2) Fortran (e.g., OpenMP [including offload] and OpenACC), (3) Python (e.g., numba, Numba, cuPy, and pyCUDA), and (4) Julia (e.g., Threads, CUDA.jl, AMDGPU.jl, and KernelAbstractions.jl). We use the GitHub Copilot capabilities powered by OpenAI Codex available in Visual Studio Code as of April 2023 to generate a vast amount of implementations given simple <kernel> + <programming model> + <optional hints> prompt variants. To quantify and compare the results, we propose a proficiency metric around the initial 10 suggestions given for each prompt. Results suggest that the OpenAI Codex outputs for C++ correlate with the adoption and maturity of programming models. For example, OpenMP and CUDA score really high, whereas HIP is still lacking. We found that prompts from either a targeted language such as Fortran or the more general-purpose Python can benefit from adding code keywords, while Julia prompts perform acceptably well for its mature programming models (e.g., Threads and CUDA.jl). We expect for these benchmarks to provide a point of reference for each programming model's community. Overall, understanding the convergence of large language models, AI, and HPC is crucial due to its rapidly evolving nature and how it is redefining human-computer interactions.
+Date: 27 Jun 2023
+
+Title: Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation
+
+Abstract Link: https://arxiv.org/abs/2306.15121
+
+PDF Link: https://arxiv.org/pdf/2306.15121
+
+Date: 27 Mar 2020
+
+Title: Detecting and Characterizing Bots that Commit Code
+
+Abstract Link: https://arxiv.org/abs/2003.03172
+
+PDF Link: https://arxiv.org/pdf/2003.03172
+
+Date: 05 Feb 2022
+
+Title: High-performance symbolic-numerics via multiple dispatch
+
+Abstract Link: https://arxiv.org/abs/2105.03949
+
+PDF Link: https://arxiv.org/pdf/2105.03949
+
+Date: 12 Apr 2022
+
+Title: Learning to Represent Programs with Heterogeneous Graphs
+
+Abstract Link: https://arxiv.org/abs/2012.04188
+
+PDF Link: https://arxiv.org/pdf/2012.04188
+
+Date: 11 Jul 2023
+
+Title: DyCL: Dynamic Neural Network Compilation Via Program Rewriting and Graph Optimization
+
+Abstract Link: https://arxiv.org/abs/2307.04963
+
+PDF Link: https://arxiv.org/pdf/2307.04963
+
+Date: 21 Jan 2021
+
+Title: PyGlove: Symbolic Programming for Automated Machine Learning
+
+Abstract Link: https://arxiv.org/abs/2101.08809
+
+PDF Link: https://arxiv.org/pdf/2101.08809
+
+Date: 26 Nov 2022
+
+Title: Sketch2FullStack: Generating Skeleton Code of Full Stack Website and Application from Sketch using Deep Learning and Computer Vision
+
+Abstract Link: https://arxiv.org/abs/2211.14607
+
+PDF Link: https://arxiv.org/pdf/2211.14607
+
+Date: 25 May 2023
+
+Title: Code as Policies: Language Model Programs for Embodied Control
+
+Abstract Link: https://arxiv.org/abs/2209.07753
+
+PDF Link: https://arxiv.org/pdf/2209.07753
+
+Date: 30 Nov 2023
+
+Title: CADTalk: An Algorithm and Benchmark for Semantic Commenting of CAD Programs
+
+Abstract Link: https://arxiv.org/abs/2311.16703
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+PDF Link: https://arxiv.org/pdf/2311.16703
+
+Date: 27 Jan 2020
+
+Title: CodeReef: an open platform for portable MLOps, reusable automation actions and reproducible benchmarking
+
+Abstract Link: https://arxiv.org/abs/2001.07935
+
+PDF Link: https://arxiv.org/pdf/2001.07935
+
+Date: 10 Jul 2023
+
+Title: COMEX: A Tool for Generating Customized Source Code Representations
+
+Abstract Link: https://arxiv.org/abs/2307.04693
+
+PDF Link: https://arxiv.org/pdf/2307.04693
+
+Date: 10 Jul 2023
+
+Title: AmadeusGPT: a natural language interface for interactive animal behavioral analysis
+
+Abstract Link: https://arxiv.org/abs/2307.04858
+
+PDF Link: https://arxiv.org/pdf/2307.04858
+
+Date: 19 Mar 2021
+
+Title: API2Com: On the Improvement of Automatically Generated Code Comments Using API Documentations
+
+Abstract Link: https://arxiv.org/abs/2103.10668
+
+PDF Link: https://arxiv.org/pdf/2103.10668
+
+Date: 29 Oct 2020
+
+Title: IntelliCode Compose: Code Generation Using Transformer
+
+Abstract Link: https://arxiv.org/abs/2005.08025
+
+PDF Link: https://arxiv.org/pdf/2005.08025
+
+Date: 22 Mar 2022
+
+Title: Demo of the Linguistic Field Data Management and Analysis System -- LiFE
+
+Abstract Link: https://arxiv.org/abs/2203.11443
+
+PDF Link: https://arxiv.org/pdf/2203.11443
+
+Date: 30 Jan 2024
+
+Title: ReactGenie: A Development Framework for Complex Multimodal Interactions Using Large Language Models
+
+Abstract Link: https://arxiv.org/abs/2306.09649
+
+PDF Link: https://arxiv.org/pdf/2306.09649
+
+Date: 09 Feb 2024
+
+Title: Model Editing with Canonical Examples
+
+Abstract Link: https://arxiv.org/abs/2402.06155
+
+PDF Link: https://arxiv.org/pdf/2402.06155
+
+Date: 11 Jun 2021
+
+Title: PyGAD: An Intuitive Genetic Algorithm Python Library
+
+Abstract Link: https://arxiv.org/abs/2106.06158
+
+PDF Link: https://arxiv.org/pdf/2106.06158
+
+Date: 27 Nov 2020
+
+Title: ROS Based Visual Programming Tool for Mobile Robot Education and Applications
+
+Abstract Link: https://arxiv.org/abs/2011.13706
+
+PDF Link: https://arxiv.org/pdf/2011.13706
+
+Date: 28 Sep 2021
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+Title: A Toolkit for Generating Code Knowledge Graphs
+
+Abstract Link: https://arxiv.org/abs/2002.09440
+
+PDF Link: https://arxiv.org/pdf/2002.09440
+
+
+
 """)