2 citations · 5 across the 6 of their papers we have counts for
6 papers
Reactor Optimization Benchmark by Reinforcement Learning
Deborah Schwarcz, Nadav Schneider, Gal Oren +1
Neutronic calculations for reactors are a daunting task when using Monte Carlo (MC) methods. As high-performance computing has advanced, the simulation of a reactor is nowadays mor…
MPIrigen: MPI Code Generation through Domain-Specific Language Models
Nadav Schneider, Niranjan Hasabnis, Vy A. Vo +9
The imperative need to scale computation across numerous nodes highlights the significance of efficient parallel computing, particularly in the realm of Message Passing Interface (…
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…
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…
Hate Speech Targets Detection in Parler using BERT
Nadav Schneider, Shimon Shouei, Saleem Ghantous +1
Online social networks have become a fundamental component of our everyday life. Unfortunately, these platforms are also a stage for hate speech. Popular social networks have regul…
Determining HEDP Foams' Quality with Multi-View Deep Learning Classification
Nadav Schneider, Matan Rusanovsky, Raz Gvishi +1
High energy density physics (HEDP) experiments commonly involve a dynamic wave-front propagating inside a low-density foam. This effect affects its density and hence, its transpare…