12 papers
Fast and Memory-Efficient Wavelet Convolutions via I/O-Aware Reformulation
Amit Aflalo, Shahaf E. Finder, Roy Amoyal +2
Wavelet convolution (WTConv) has emerged as an increasingly popular drop-in replacement for standard convolutions, expanding a network's receptive field exponentially with the numb…
RAPNet: Accelerating Algebraic Multigrid with Learned Sparse Corrections
Yali Fink, Ido Ben-Yair, Lars Ruthotto +1
The scalable solution of large sparse linear systems is a bottleneck in scientific computing and graph analysis. While algebraic multigrid (AMG) offers optimal linear scaling, its…
Scalable Multigrid Solver for the Helmholtz Equation: Real-Shifted Coarse Grid Correction
Rachel Yovel, Eran Treister
We present a convergent and scalable multigrid solver for high-frequency Helmholtz equations. Standard multigrid methods do not converge for high-frequency Helmholtz problems, and…
A SIMPLE-Based Preconditioned Solver for the Direct-Forcing Immersed Boundary Method
Rachel Yovel, Eran Treister, Yuri Feldman
We present a robust and scalable solver for direct-forcing immersed boundary simulations, based on a preconditioned SIMPLE algorithm. The method applies block elimination to the pr…
A block-acoustic preconditioner for the elastic Helmholtz equation
Rachel Yovel, Eran Treister
We present a novel block-preconditioner for the elastic Helmholtz equation, based on a reduction to acoustic Helmholtz equations. Both versions of the Helmholtz equations are chall…
Reversing Large Language Models for Efficient Training and Fine-Tuning
Eshed Gal, Moshe Eliasof, Javier Turek +3
Large Language Models (LLMs) are known for their expensive and time-consuming training. Thus, oftentimes, LLMs are fine-tuned to address a specific task, given the pretrained weigh…