SPX: Enabling Scalable Synchronizations for General Purpose GPUs

SPX：为通用 GPU 启用可扩展同步

• 批准号: 1725657
• 负责人: Jun Yang
• 金额: $ 85万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1725657&HistoricalAwards=false
• 关键词: SPX; Enabling; Scalable; Synchronizations; General

Today?s GPUs have been successfully used for general purpose processing including high-performance computing, machine learning, graph analytics, to name a few applications. However, general purpose computing has different complexity and characteristics from those of graphics processing. A crucial characteristic is the need for coordination and synchronization among parallel threads, which occurs more often in general purpose applications than in graphics rendering. However, unlike common CPU designs, current GPU designs are missing full-fledged support for synchronization primitives that are convenient for implementing transparent scalability and achieving high performance for many parallel applications.This project develops truly effective, efficient, easy-to-use and easy-to-implement synchronization mechanisms for GPGPU while overcoming major obstacles pertaining to the GPU architecture. The first thrust will identify GPGPU synchronization primitives that are deemed sufficient to handle a large set of applications with static and dynamic dependencies. The second thrust will provide solutions and methodologies on how to use the new primitives in the most efficient way to suit the characteristics of applications. The third thrust addresses the main challenges in implementing those primitives in efficiency, possible context switching overhead, and memory capacity limitations. The success in this project will help fuel the spread of accelerator architectures for high-performance computing, cloud and mobile systems. It will increase efficiency for improved performance and reduced energy/power consumption, leading to a greener IT industry. Trained students will become future taskforce to continue the revolution of extending computing into every realm of science, life, commerce and culture.

今天吗？的GPU已成功用于通用处理，包括高性能计算、机器学习、图形分析等应用。然而，通用计算具有与图形处理不同的复杂性和特征。一个关键的特性是需要在并行线程之间进行协调和同步，这在通用应用程序中比在图形渲染中更常见。然而，与普通的CPU设计不同，目前的GPU设计缺少对同步原语的全面支持，这些原语便于实现透明的可扩展性并为许多并行应用实现高性能。本项目为GPGPU开发真正有效，高效，易于使用和易于实现的同步机制，同时克服与GPU架构相关的主要障碍。第一个推力将确定GPGPU同步原语，这些原语被认为足以处理大量具有静态和动态依赖关系的应用程序。第二个重点将提供关于如何以最有效的方式使用新原语以适应应用程序特性的解决方案和方法。第三个推力解决了在实现这些原语的效率、可能的上下文切换开销和内存容量限制方面的主要挑战。该项目的成功将有助于推动高性能计算、云和移动的系统加速器架构的推广。它将提高效率，改善性能，降低能源/功耗，从而实现更环保的IT行业。经过培训的学生将成为未来的工作队，继续将计算扩展到科学，生活，商业和文化的各个领域的革命。

项目成果

PageCmp: Bandwidth Efficient Page Deduplication through In-memory Page Comparison

PageCmp：通过内存中页面比较实现带宽高效的页面重复数据删除

• DOI: 10.1109/isvlsi.2019.00023
• 发表时间: 2019
• 期刊: 2019 IEEE Computer Society Annual Symposium on VLSI
• 作者: Raoufi, Mehrnoosh;Deng, Quan;Zhang, Youtao;Yang, Jun
• 通讯作者: Yang, Jun

CacheTree: Reducing Integrity Verification Overhead of Secure Nonvolatile Memories

CacheTree：减少安全非易失性存储器的完整性验证开销

• DOI: 10.1109/tcad.2020.3015925
• 发表时间: 2021-07-01
• 期刊: IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS
• 影响因子: 2.9
• 作者: Chen, Zhengguo;Zhang, Youtao;Xiao, Nong
• 通讯作者: Xiao, Nong

Parallel all the time: Plane Level Parallelism Exploration for High Performance SSDs

• DOI: 10.1109/msst.2019.000-5
• 发表时间: 2019-05
• 期刊: 2019 35th Symposium on Mass Storage Systems and Technologies (MSST)
• 作者: Congming Gao;Liang Shi;C. Xue;Cheng Ji;Jun Yang;Youtao Zhang

Holistic energy efficient crosstalk mitigation in DRAM

DRAM 中的整体节能串扰缓解

• DOI: 10.1109/igcc.2017.8323590
• 发表时间: 2019
• 期刊: Eighth Annual International Green and Sustainable Computing Conference
• 作者: Jones, Alex K.;Melhem, Rami;Kline, Donald
• 通讯作者: Kline, Donald

Improving Address Translation in Multi-GPUs via Sharing and Spilling aware TLB Design

• DOI: 10.1145/3466752.3480083
• 发表时间: 2021-10
• 期刊: MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture
• 作者: Bingyao Li;Jieming Yin;Youtao Zhang;Xulong Tang