A Mixed Precision, Multi-GPU Design for Large-scale Top-K Sparse Eigenproblems

Solving Large Top-K Graph Eigenproblems with a Memory and Compute-optimized FPGA Design

Large-scale eigenvalue computations on sparse matrices are a key component of graph analytics techniques based on spectral methods. In such applications, an exhaustive computation of all eigenvalues and eigenvectors is impractical and unnecessary, as spectral methods can retrieve the relevant properties of enormous graphs using just the eigenvectors associated with the Top-K largest eigenvalues. In this work, we propose a hardware-optimized algorithm to approximate a solution to the Top-K eigenproblem on sparse matrices representing large graph topologies. We prototype our algorithm through a …

面向AI时代的下一代异步分布式GPU架构设计

Architecting the Next Generation of Asynchronous, Distributed GPUs for the AI Era

针对AI时代GPU架构模拟基础设施滞后的问题，提出可建模Ampere等现代GPU的周期级模拟框架，经H100验证精度达标，用于评估小芯片拓扑等新兴设计轨迹。

GPU增强的OLAP执行引擎：GPU卸载

GPU-Augmented OLAP Execution Engine: GPU Offloading

本文提出一种GPU增强的OLAP执行引擎，通过风险感知门控机制选择性卸载高影响原语以提升执行效率。

NUNA：表征与缓解多芯片GPU扩展系统中的非统一网络访问

NUNA: Characterizing and Mitigating Non-Uniform Network Access in Multi-Die GPU Scale-Up Systems

该研究针对多芯片GPU扩展系统中未被充分研究的非统一网络访问（NUNA）问题，提出感知NUNA的路由（NAR）与布局（NAP）方法，可将机器学习推理的集体通信加速最高达1.8倍，每输出token时间最大提升28%。

Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect

High performance multi-GPU computing becomes an inevitable trend due to the ever-increasing demand on computation capability in emerging domains such as deep learning, big data and planet-scale simulations. However, the lack of deep understanding on how modern GPUs can be connected and the real impact of state-of-the-art interconnect technology on multi-GPU application performance become a hurdle. In this paper, we fill the gap by conducting a thorough evaluation on five latest types of modern GPU interconnects: PCIe, NVLink-V1, NVLink-V2, NVLink-SLI and NVSwitch, from six high-end servers and…