activity
20232025
most citedStratum: System-Hardware Co-Design with Tiered Monolithic 3D-Stackable DRAM for Efficient MoE Serving

7 citations · 9 across the 8 of their papers we have counts for

collaborators
Showing cs.ARShow all

6 papers · 1 filter

cs.AR2025

PIM-FW: Hardware-Software Co-Design of All-pairs Shortest Paths in DRAM

Tsung-Han Lu, Zheyu Li, Minxuan Zhou +1

All-pairs shortest paths (APSP) is a fundamental algorithm used for routing, logistics, and network analysis, but the cubic time complexity and heavy data movement of the canonical…

cs.AR2025

RAPID-Graph: Recursive All-Pairs Shortest Paths Using Processing-in-Memory for Dynamic Programming on Graphs

Yanru Chen, Zheyu Li, Keming Fan +5

All-pairs shortest paths (APSP) remains a major bottleneck for large-scale graph analytics, as data movement with cubic complexity overwhelms the bandwidth of conventional memory h…

cs.AR2025★ 7 cited

Stratum: System-Hardware Co-Design with Tiered Monolithic 3D-Stackable DRAM for Efficient MoE Serving

Yue Pan, Zihan Xia, Po-Kai Hsu +8

As Large Language Models (LLMs) continue to evolve, Mixture of Experts (MoE) architecture has emerged as a prevailing design for achieving state-of-the-art performance across a wid…

cs.AR2024

Fast-OverlaPIM: A Fast Overlap-driven Mapping Framework for Processing In-Memory Neural Network Acceleration

Xuan Wang, Minxuan Zhou, Tajana Rosing

Processing in-memory (PIM) is promising to accelerate neural networks (NNs) because it minimizes data movement and provides large computational parallelism. Similar to machine lear…

cs.AR2023★ 2 cited

Proxima: Near-storage Acceleration for Graph-based Approximate Nearest Neighbor Search in 3D NAND

Weihong Xu, Junwei Chen, Po-Kai Hsu +5

Approximate nearest neighbor search (ANNS) plays an indispensable role in a wide variety of applications, including recommendation systems, information retrieval, and semantic sear…

cs.AR2023

FHEmem: A Processing In-Memory Accelerator for Fully Homomorphic Encryption

Minxuan Zhou, Yujin Nam, Pranav Gangwar +7

Fully Homomorphic Encryption (FHE) is a technique that allows arbitrary computations to be performed on encrypted data without the need for decryption, making it ideal for securing…