6 papers
Scaled Block Vecchia Approximation for High-Dimensional Gaussian Process Emulation on GPUs
Qilong Pan, Sameh Abdulah, Mustafa Abduljabbar +8
Emulating computationally intensive scientific simulations is crucial for enabling uncertainty quantification, optimization, and informed decision-making at scale. Gaussian Process…
RAP: KV-Cache Compression via RoPE-Aligned Pruning
Jihao Xin, Tian Lyu, David Keyes +2
Long-context inference in large language models (LLMs) is bottlenecked by the memory and compute of the key-value (KV) cache. Structured pruning is a direct way to shrink it: dropp…
GPU-Accelerated Parallel Selected Inversion for Structured Matrices Using sTiles
Esmail Abdul Fattah, Hatem Ltaief, Havard Rue +1
Selected inversion is essential for applications such as Bayesian inference, electronic structure calculations, and inverse covariance estimation, where computing only specific ele…
GPU-Accelerated Modified Bessel Function of the Second Kind for Gaussian Processes
Zipei Geng, Sameh Abdulah, Ying Sun +3
Modified Bessel functions of the second kind are widely used in physics, engineering, spatial statistics, and machine learning. Since contemporary scientific applications, includin…
sTiles: An Accelerated Computational Framework for Sparse Factorizations of Structured Matrices
Esmail Abdul Fattah, Hatem Ltaief, Havard Rue +1
This paper introduces sTiles, a GPU-accelerated framework for factorizing sparse structured symmetric matrices. By leveraging tile algorithms for fine-grained computations, sTiles…
Accelerating Mixed-Precision Out-of-Core Cholesky Factorization with Static Task Scheduling
Jie Ren, Hatem Ltaief, Sameh Abdulah +1
This paper explores the performance optimization of out-of-core (OOC) Cholesky factorization on shared-memory systems equipped with multiple GPUs. We employ fine-grained computatio…