187 citations · 287 across the 13 of their papers we have counts for
14 papers
Scope is all you need: Transforming LLMs for HPC Code
Tal Kadosh, Niranjan Hasabnis, Vy A. Vo +9
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 addres…
Quantifying OpenMP: Statistical Insights into Usage and Adoption
Tal Kadosh, Niranjan Hasabnis, Timothy Mattson +2
In high-performance computing (HPC), the demand for efficient parallel programming models has grown dramatically since the end of Dennard Scaling and the subsequent move to multi-c…
Advising OpenMP Parallelization via a Graph-Based Approach with Transformers
Tal Kadosh, Nadav Schneider, Niranjan Hasabnis +3
There is an ever-present need for shared memory parallelization schemes to exploit the full potential of multi-core architectures. The most common parallelization API addressing th…
MPI-rical: Data-Driven MPI Distributed Parallelism Assistance with Transformers
Nadav Schneider, Tal Kadosh, Niranjan Hasabnis +3
Message Passing Interface (MPI) plays a crucial role in distributed memory parallelization across multiple nodes. However, parallelizing MPI code manually, and specifically, perfor…
Introducing the Quantum Research Kernels: Lessons from Classical Parallel Computing
A. Y. Matsuura, Timothy G. Mattson
Quantum computing represents a paradigm shift for computation requiring an entirely new computer architecture. However, there is much that can be learned from traditional classical…
LAGraph: Linear Algebra, Network Analysis Libraries, and the Study of Graph Algorithms
Gábor Szárnyas, David A. Bader, Timothy A. Davis +4
Graph algorithms can be expressed in terms of linear algebra. GraphBLAS is a library of low-level building blocks for such algorithms that targets algorithm developers. LAGraph bui…