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cs.DC2026

Parallelizing the Approximate Minimum Degree Ordering Algorithm: Strategies and Evaluation

Yen-Hsiang Chang, Aydın Buluç, James Demmel

The approximate minimum degree algorithm is widely used before numerical factorization to reduce fill-in for sparse matrices. While considerable attention has been given to the num…

cs.DC2025

Fast Algorithms for Scheduling Many-body Correlation Functions on Accelerators

Oguz Selvitopi, Emin Ozturk, Jie Chen +3

Computation of correlation functions is a key operation in Lattice quantum chromodynamics (LQCD) simulations to extract nuclear physics observables. These functions involve many bi…

cs.DC2025

Distributed-Memory Parallel Algorithms for Fixed-Radius Near Neighbor Graph Construction

Gabriel Raulet, Dmitriy Morozov, Aydin Buluc +1

Computing fixed-radius near-neighbor graphs is an important first step for many data analysis algorithms. Near-neighbor graphs connect points that are close under some metric, endo…

cs.DC2025

Parallel GPU-Accelerated Randomized Construction of Approximate Cholesky Preconditioners

Tianyu Liang, Chao Chen, Yotam Yaniv +5

We introduce a parallel algorithm to construct a preconditioner for solving a large, sparse linear system where the coefficient matrix is a Laplacian matrix (a.k.a., graph Laplacia…

cs.DC2024

A sparsity-aware distributed-memory algorithm for sparse-sparse matrix multiplication

Yuxi Hong, Aydin Buluc

Multiplying two sparse matrices (SpGEMM) is a common computational primitive used in many areas including graph algorithms, bioinformatics, algebraic multigrid solvers, and randomi…

cs.DC2024

RDMA-Based Algorithms for Sparse Matrix Multiplication on GPUs

Benjamin Brock, Aydın Buluç, Katherine Yelick

Sparse matrix multiplication is an important kernel for large-scale graph processing and other data-intensive applications. In this paper, we implement various asynchronous, RDMA-b…