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Preprint Sep 2026

Distributed Linear Programming on GPU Clusters at Extreme Scale

SHARDLP is presented, a distributed GPU LP solver that keeps the matrix and primal-dual state partitioned from sharded input through solution output and reaches the published criterion on nine of eleven instances, on the Google PDLP benchmark.

Arnaud Deza, S. Dey, P. Van Hentenryck · 1 citation
Open access Sep 2026

Bullseye Hash: An Efficient Hash-Table for Sparse Tensor Contraction

This work proposes Bullseye Hash, a novel hash table designed to efficiently support SpTC computations and provides guidance on configuring data object representations based on their specific characteristics, considering both algorithmic complexity and cache efficiency.

Guo-Feng Feng, Ze-Cheng Li, Ming-Zhen Li et al. · 0 citations
Preprint Sep 2026

Every Kernel Is a Join: Automatic Multi-GPU Parallelism for AI Computations in Einsummable

Distributing an AI computation across the GPUs of a multi-GPU server is one of the central problems in systems-for-AI. We present Einsummable, a prototype system that accepts a PyTorch-like description of an AI computation and automatically distributes it across a multi-GPU server, with no device assignments, sharding...

Zhi-Min Ding, Chen-Kuan Liao, Chima Adiole et al. · 0 citations
Preprint Aug 2026

Billion-Scale Nearest-Neighbor Search under Fully Homomorphic Encryption on a Single GPU, Balancing Leakage and Cost

A system that answers "which database vectors are most similar to my query?" without the server ever seeing the query is built, and what this speed costs is measured: the hierarchy's access pattern leaks the database geometry, and it is shown that seeded padding cuts this leak by ~35x.

I. Isozaki, Madison Bratina, Edward Kim · 0 citations
Book Open access Sep 2026

BAG: Faster Matrix Multiplication on a Single GPU

BAG (Basis Alternative Matrix Multiplication on GPUs), a GPU-oriented implementation of ABMM for the NVIDIA Ampere architecture is presented, designed to shrink workspace and eliminate redundant global-memory traffic, and introduce a cost-model-based recursion policy together with a Roofline-guided blocking strategy to...

Yao Liu, Ye-Wen Li, Zhong-Hai Zhang et al. · 0 citations
#machine learning Preprint Oct 2026

PageWeaver: KV-Guided Query Unions for Sparse Attention

Dynamic sparse attention limits the KV pages selected by each query, but a small support does not necessarily yield efficient GPU work. Query unions share page loads and populate Tensor Core tiles; their cost depends on which queries are grouped together. We present PageWeaver, an execution design that uses selected-pa...

Zhi-Yuan Li, Zi-Han Li, Ze-Fang Yuan et al. · 0 citations

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