SPX: Collaborative Research: Harnessing the Power of High-Bandwidth Memory via Provably Efficient Parallel Algorithms
SPX: Collaborative Research: Harnessing the Power of High-Bandwidth Memory via Provably Efficient Parallel Algorithms
批准号:
1824303
负责人:
Benjamin Moseley
金额:
$25.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-01-01 至 2022-08-31
中文摘要
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英文摘要
An important bottleneck for many parallel scientific applications is memory performance. Recently, vendors have introduced a new memory called high-bandwidth memory (HBM) as an approach to alleviate this bottleneck. This project will develop an algorithmic foundation for using HBM. The project has the potential for a broad economic, technological, and scientific impact, since industry has an investment in this technology and many of the nation's strategic codes are being run on HBM-capable machines. The PIs will integrate research with education at the graduate and undergraduate levels by training PhD, MS, and honors program BS students in cross-cutting issues encompassing algorithm design, high-performance software, and processor architecture. The new approach offered by vendors is to bond memory (HBM) directly to the processor chip, which allows for more connections, enabling higher bandwidth. Although the size of the new memory is larger than modern on-chip caches, physical constraints limit the capacity of the memory to be significantly smaller than DRAM. HBM does not cleanly fit in the standard memory hierarchy. This project will develop a foundational understanding of how to algorithmically design codes for HBM enhanced architectures. Overcoming these intellectual challenges to achieve multi-core scalability using HBM requires new algorithms, models, and abstractions, spearheaded by this collaboration between researchers who study hardware issues, high performance computing challenges, and theoretical modeling and analysis.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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DOI:
10.1007/978-3-030-46150-8_5
发表时间:
2019-09
期刊:
影响因子:
--
作者:
[Silvio Lattanzi;Thomas Lavastida;Kefu Lu;Benjamin Moseley]
通讯作者:
Silvio Lattanzi;Thomas Lavastida;Kefu Lu;Benjamin Moseley
Practically Efficient Scheduler for Minimizing Average Flow Time of Parallel Jobs
实用高效的调度程序,可最大限度地减少并行作业的平均流程时间
DOI:
10.1109/ipdps.2019.00024
发表时间:
2019
期刊:
2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS
影响因子:
--
作者:
[Agrawal, Kunal, Lee, I-Ting Angelina, Li, Jing, Lu, Kefu, Moseley, Benjamin]
通讯作者:
Moseley, Benjamin
DOI:
--
发表时间:
2021
期刊:
影响因子:
--
作者:
[Silvio Lattanzi;Benjamin Moseley;Sergei Vassilvitskii;Yuyan Wang;Rudy Zhou]
通讯作者:
Silvio Lattanzi;Benjamin Moseley;Sergei Vassilvitskii;Yuyan Wang;Rudy Zhou
DOI:
10.1137/1.9781611975994.114
发表时间:
2020-01
期刊:
The FASEB Journal
影响因子:
--
作者:
[Silvio Lattanzi;Thomas Lavastida;Benjamin Moseley;Sergei Vassilvitskii]
通讯作者:
Silvio Lattanzi;Thomas Lavastida;Benjamin Moseley;Sergei Vassilvitskii
Scheduling to Approximate Minimization Objectives on Identical Machines
在相同机器上实现近似最小化目标的调度
DOI:
--
发表时间:
2019
期刊:
and Programming (ICALP 2019
影响因子:
--
作者:
[Moseley, Benjamin]
通讯作者:
Moseley, Benjamin
共 38 条
Collaborative Research: AF: Small: Foundations of Algorithms Augmented with Predictions
-
批准号:2121744
-
项目类别:Standard Grant
-
资助金额:$25.0万
-
财政年份:2022
-
负责人:Benjamin Moseley
-
依托单位:
CAREER: Pushing the Theoretical Limits of Scalable Distributed Algorithms
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批准号:1845146
-
项目类别:Continuing Grant
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资助金额:$50.0万
-
财政年份:2019
-
负责人:Benjamin Moseley
-
依托单位:
AF: Small: Collaborative Research: Algorithmic and Computational Frontiers of MapReduce for Big Data Analysis
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批准号:1830711
-
项目类别:Standard Grant
-
资助金额:$11.45万
-
财政年份:2018
-
负责人:Benjamin Moseley
-
依托单位:
SPX: Collaborative Research: Harnessing the Power of High-Bandwidth Memory via Provably Efficient Parallel Algorithms
-
批准号:1725661
-
项目类别:Standard Grant
-
资助金额:$25.0万
-
财政年份:2017
-
负责人:Benjamin Moseley
-
依托单位:
AF: Small: Collaborative Research: Algorithmic and Computational Frontiers of MapReduce for Big Data Analysis
-
批准号:1617724
-
项目类别:Standard Grant
-
资助金额:$25.28万
-
财政年份:2016
-
负责人:Benjamin Moseley
-
依托单位:
海外基金