:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Shen, Ao, Zhang, Rui, Zhao, Junping
Format:	Preprint
Published:	2025
Subjects:	Hardware Architecture Artificial Intelligence Distributed, Parallel, and Cluster Computing Machine Learning
Online Access:	https://arxiv.org/abs/2510.15882
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Flex-TPU: A Flexible TPU with Runtime Reconfigurable Dataflow Architecture
by: Elbtity, Mohammed, et al.
Published: (2024)

Advancing AI-assisted Hardware Design with Hierarchical Decentralized Training and Personalized Inference-Time Optimization
by: Chen, Hao Mark, et al.
Published: (2025)

TeraPool: A Physical Design Aware, 1024 RISC-V Cores Shared-L1-Memory Scaled-up Cluster Design with High Bandwidth Main Memory Link
by: Zhang, Yichao, et al.
Published: (2026)

TCDM Burst Access: Breaking the Bandwidth Barrier in Shared-L1 RVV Clusters Beyond 1000 FPUs
by: Shen, Diyou, et al.
Published: (2025)

HyperOffload: Graph-Driven Hierarchical Memory Management for Large Language Models on SuperNode Architectures
by: Liu, Fangxin, et al.
Published: (2026)

Tangram: Accelerating Serverless LLM Loading through GPU Memory Reuse and Affinity
by: Zhu, Wenbin, et al.
Published: (2025)

Heterogeneous Computing: The Key to Powering the Future of AI Agent Inference
by: Zhao, Yiren, et al.
Published: (2026)

The Hitchhiker's Guide to Programming and Optimizing Cache Coherent Heterogeneous Systems: CXL, NVLink-C2C, and AMD Infinity Fabric
by: Wang, Zixuan, et al.
Published: (2024)

SnapStream: Efficient Long Sequence Decoding on Dataflow Accelerators
by: Li, Jonathan, et al.
Published: (2025)

HPU: High-Bandwidth Processing Unit for Scalable, Cost-effective LLM Inference via GPU Co-processing
by: Rhee, Myunghyun, et al.
Published: (2025)

CUTEv2: Unified and Configurable Matrix Extension for Diverse CPU Architectures with Minimal Design Overhead
by: Ye, Jinpeng, et al.
Published: (2026)

PIM-Opt: Demystifying Distributed Optimization Algorithms on a Real-World Processing-In-Memory System
by: Rhyner, Steve, et al.
Published: (2024)

Sustainable Supercomputing for AI: GPU Power Capping at HPC Scale
by: Zhao, Dan, et al.
Published: (2024)

Serving Large Language Models on Huawei CloudMatrix384
by: Zuo, Pengfei, et al.
Published: (2025)

TriMoE: Augmenting GPU with AMX-Enabled CPU and DIMM-NDP for High-Throughput MoE Inference via Offloading
by: Pan, Yudong, et al.
Published: (2026)

DCO: Dynamic Cache Orchestration for LLM Accelerators through Predictive Management
by: Zhou, Zhongchun, et al.
Published: (2025)

Rearchitecting Datacenter Lifecycle for AI: A TCO-Driven Framework
by: Stojkovic, Jovan, et al.
Published: (2025)

NPU Design for Diffusion Language Model Inference
by: Lou, Binglei, et al.
Published: (2026)

DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency
by: Stojkovic, Jovan, et al.
Published: (2024)

Intent-Driven Storage Systems: From Low-Level Tuning to High-Level Understanding
by: Bergman, Shai, et al.
Published: (2025)

Mooncake: A KVCache-centric Disaggregated Architecture for LLM Serving
by: Qin, Ruoyu, et al.
Published: (2024)

Investigating Memory Failure Prediction Across CPU Architectures
by: Yu, Qiao, et al.
Published: (2024)

ZettaLith: An Architectural Exploration of Extreme-Scale AI Inference Acceleration
by: Silverbrook, Kia
Published: (2025)

Enabling Accelerators for Graph Computing
by: Shivdikar, Kaustubh
Published: (2023)

SLO-aware GPU Frequency Scaling for Energy Efficient LLM Inference Serving
by: Kakolyris, Andreas Kosmas, et al.
Published: (2024)

Patterns behind Chaos: Forecasting Data Movement for Efficient Large-Scale MoE LLM Inference
by: Yu, Zhongkai, et al.
Published: (2025)

MIST: A Co-Design Framework for Heterogeneous, Multi-Stage LLM Inference
by: Bambhaniya, Abhimanyu Rajeshkumar, et al.
Published: (2025)

Accelerating Sampling and Aggregation Operations in GNN Frameworks with GPU Initiated Direct Storage Accesses
by: Park, Jeongmin Brian, et al.
Published: (2023)

Demystifying AI Platform Design for Distributed Inference of Next-Generation LLM models
by: Bambhaniya, Abhimanyu, et al.
Published: (2024)

Sustainable AI Training via Hardware-Software Co-Design on NVIDIA, AMD, and Emerging GPU Architectures
by: Makin, Yashasvi, et al.
Published: (2025)

PREBA: A Hardware/Software Co-Design for Multi-Instance GPU based AI Inference Servers
by: Yeo, Gwangoo, et al.
Published: (2024)

AMMA: A Multi-Chiplet Memory-Centric Architecture for Low-Latency 1M Context Attention Serving
by: Yu, Zhongkai, et al.
Published: (2026)

Splitwiser: Efficient LM inference with constrained resources
by: Aali, Asad, et al.
Published: (2025)

Sensitivity-Guided Framework for Pruned and Quantized Reservoir Computing Accelerators
by: Jafari, Atousa, et al.
Published: (2026)

PAPI: Exploiting Dynamic Parallelism in Large Language Model Decoding with a Processing-In-Memory-Enabled Computing System
by: He, Yintao, et al.
Published: (2025)

ELMoE-3D: Leveraging Intrinsic Elasticity of MoE for Hybrid-Bonding-Enabled Self-Speculative Decoding in On-Premises Serving
by: Choi, Yuseon, et al.
Published: (2026)

Online GPU Energy Optimization with Switching-Aware Bandits
by: Xu, Xiongxiao, et al.
Published: (2024)

Hybrid Offline-online Scheduling Method for Large Language Model Inference Optimization
by: Pang, Bowen, et al.
Published: (2025)

VLSI Hypergraph Partitioning with Deep Learning
by: Khan, Muhammad Hadir, et al.
Published: (2024)

FlexStep: Enabling Flexible Error Detection in Multi/Many-core Real-time Systems
by: Wang, Tinglue, et al.
Published: (2025)