Toward More Energy-Efficient Datacenters with Enhanced Programmable Silicon
利用增强型可编程芯片打造更节能的数据中心
基本信息
- 批准号:RGPIN-2016-05537
- 负责人:
- 金额:$ 3.93万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2020
- 资助国家:加拿大
- 起止时间:2020-01-01 至 2021-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The ability to fabricate ever more transistors on a semiconductor chip has enabled ever more computation, transforming society with ubiquitous communications, advanced medical imaging, on-demand entertainment delivery and more. We have become accustomed to the cost and energy of computation dropping exponentially over time, enabling new applications and societal benefits that motivate investment in raising computational capabilities further. This virtuous cycle is now under threat as the energy required for a computation no longer drops sufficiently with improved manufacturing of conventional processors (CPUs). There is an alternative: configure specialized hardware into Field Programamble Gate Array (FPGA) chips instead of controlling general CPU hardware with software instructions. This allows FPGAs to use 10% or less of the energy required by a CPU for many computations.
However, FPGAs face their own challenges. First, it is harder to design an application to run on an FPGA than on a CPU, and as improved manufacturing continually increases the logic capacity of FPGAs it is becoming very time-consuming to complete designs that fully utilize them. Second, increasingly computation is moving from special purpose systems such as cell phone base stations, which often employ FPGAs, to centralized data centers, which today almost exclusively use CPUs. Moving computation to data centers enables centralized administration and hardware sharing but Data centers consume tremendous amounts of power (~2% of US electricity demand). They could greatly benefit from the energy-efficiency of FPGAs, but the difficulty of FPGA application design and sharing between applications have limited their use in data centers.
We will make today's high-capacity FPGAs easier to use by creating new modular software tools that let engineers easily connect smaller hardware blocks to create a full application. We will also investigate embedding a communication network in the FPGA chip to make it easier still for hardware blocks to communicate. We will create a new design style that allows applications to be interrupted and swapped in and out of an FPGA over time so it can be shared. Finally, we will scale an FPGA-accelerated simulator and optimizer for light-activated chemotherapy to data center scale, and show how our new tools, FPGA architectures and swappable design style benefit this application. This will both validate our FPGA improvements and help make a promising new cancer therapy practical.
Together the innovations we propose will enable wider use of FPGAs in the data center, reducing energy, operating costs and environmental impact. Furthermore, as energy is the limiting factor in computation today, making more energy-efficient computing practical in data centers is essential for further scaling of computational capabilities, and the new applications and benefits it will enable.
在半导体芯片上制造更多晶体管的能力使更多的计算成为可能,通过无处不在的通信、先进的医学成像、按需娱乐交付等改变了社会。我们已经习惯了计算的成本和能量随着时间的推移呈指数级下降,从而实现了新的应用和社会效益,从而推动了对进一步提高计算能力的投资。这种良性循环现在正受到威胁,因为随着传统处理器(CPU)制造的改进,计算所需的能量不再充分下降。有一个替代方案:将专用硬件配置到现场可编程门阵列(FPGA)芯片中,而不是用软件指令控制通用CPU硬件。这允许FPGA使用CPU所需能量的10%或更少来进行许多计算。
然而,FPGA面临着自己的挑战。首先,设计一个在FPGA上运行的应用程序比在CPU上运行的应用程序更难,而且随着制造业的不断改进,FPGA的逻辑容量不断增加,完成充分利用FPGA的设计变得非常耗时。其次,越来越多的计算正在从专用系统(如通常使用FPGA的手机基站)转移到集中式数据中心(如今几乎完全使用CPU)。将计算转移到数据中心可以实现集中管理和硬件共享,但数据中心消耗大量电力(约占美国电力需求的2%)。它们可以从FPGA的能效中受益匪浅,但FPGA应用程序设计和应用程序之间共享的困难限制了它们在数据中心的使用。
我们将通过创建新的模块化软件工具,让工程师轻松连接较小的硬件模块,以创建完整的应用程序,从而使当今的高容量FPGA更易于使用。我们还将研究在FPGA芯片中嵌入通信网络,以使硬件模块更容易进行通信。我们将创建一种新的设计风格,允许应用程序被中断,并随着时间的推移在FPGA中交换,以便可以共享。最后,我们将把用于光激活化疗的FPGA加速模拟器和优化器扩展到数据中心规模,并展示我们的新工具、FPGA架构和可交换设计风格如何使该应用受益。这将验证我们的FPGA改进,并有助于使一种有前途的新癌症疗法成为现实。
我们提出的创新将使FPGA在数据中心中得到更广泛的使用,从而降低能源、运营成本和环境影响。此外,由于能源是当今计算的限制因素,因此在数据中心实现更节能的计算对于进一步扩展计算能力以及它将带来的新应用和好处至关重要。
项目成果
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Betz, Vaughn其他文献
Koios 2.0: Open-Source Deep Learning Benchmarks for FPGA Architecture and CAD Research
Koios 2.0:FPGA 架构和 CAD 研究的开源深度学习基准
- DOI:
10.1109/tcad.2023.3272582 - 发表时间:
2023 - 期刊:
- 影响因子:2.9
- 作者:
Arora, Aman;Boutros, Andrew;Damghani, Seyed Alireza;Mathur, Karan;Mohanty, Vedant;Anand, Tanmay;Elgammal, Mohamed A.;Kent, Kenneth B.;Betz, Vaughn;John, Lizy K. - 通讯作者:
John, Lizy K.
Tensor Slices: FPGA Building Blocks For The Deep Learning Era
张量切片:深度学习时代的 FPGA 构建模块
- DOI:
10.1145/3529650 - 发表时间:
2022 - 期刊:
- 影响因子:2.3
- 作者:
Arora, Aman;Ghosh, Moinak;Mehta, Samidh;Betz, Vaughn;John, Lizy K. - 通讯作者:
John, Lizy K.
Automatic interstitial photodynamic therapy planning via convex optimization
- DOI:
10.1364/boe.9.000898 - 发表时间:
2018-02-01 - 期刊:
- 影响因子:3.4
- 作者:
Yassine, Abdul-Amir;Kingsford, William;Betz, Vaughn - 通讯作者:
Betz, Vaughn
Treatment plan evaluation for interstitial photodynamic therapy in a mouse model by Monte Carlo simulation with FullMonte
- DOI:
10.3389/fphy.2015.00006 - 发表时间:
2015-02-24 - 期刊:
- 影响因子:3.1
- 作者:
Cassidy, Jeffrey;Betz, Vaughn;Lilge, Lothar - 通讯作者:
Lilge, Lothar
Betz, Vaughn的其他文献
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{{ truncateString('Betz, Vaughn', 18)}}的其他基金
Exploiting and Enhancing Programmable Logic for Deep Learning and Datacenter Acceleration
利用和增强可编程逻辑进行深度学习和数据中心加速
- 批准号:
RGPIN-2022-04445 - 财政年份:2022
- 资助金额:
$ 3.93万 - 项目类别:
Discovery Grants Program - Individual
Toward More Energy-Efficient Datacenters with Enhanced Programmable Silicon
利用增强型可编程芯片打造更节能的数据中心
- 批准号:
RGPIN-2016-05537 - 财政年份:2021
- 资助金额:
$ 3.93万 - 项目类别:
Discovery Grants Program - Individual
NSERC/Intel Industrial Research Chair in Programmable Silicon
NSERC/英特尔可编程芯片工业研究主席
- 批准号:
428842-2016 - 财政年份:2020
- 资助金额:
$ 3.93万 - 项目类别:
Industrial Research Chairs
Toward More Energy-Efficient Datacenters with Enhanced Programmable Silicon
利用增强型可编程芯片打造更节能的数据中心
- 批准号:
RGPIN-2016-05537 - 财政年份:2019
- 资助金额:
$ 3.93万 - 项目类别:
Discovery Grants Program - Individual
NSERC/Intel Industrial Research Chair in Programmable Silicon
NSERC/英特尔可编程芯片工业研究主席
- 批准号:
428842-2016 - 财政年份:2019
- 资助金额:
$ 3.93万 - 项目类别:
Industrial Research Chairs
Toward More Energy-Efficient Datacenters with Enhanced Programmable Silicon
利用增强型可编程芯片打造更节能的数据中心
- 批准号:
RGPIN-2016-05537 - 财政年份:2018
- 资助金额:
$ 3.93万 - 项目类别:
Discovery Grants Program - Individual
NSERC/Intel Industrial Research Chair in Programmable Silicon
NSERC/英特尔可编程芯片工业研究主席
- 批准号:
428842-2016 - 财政年份:2018
- 资助金额:
$ 3.93万 - 项目类别:
Industrial Research Chairs
Toward More Energy-Efficient Datacenters with Enhanced Programmable Silicon
利用增强型可编程芯片打造更节能的数据中心
- 批准号:
RGPIN-2016-05537 - 财政年份:2017
- 资助金额:
$ 3.93万 - 项目类别:
Discovery Grants Program - Individual
NSERC/Intel Industrial Research Chair in Programmable Silicon
NSERC/英特尔可编程芯片工业研究主席
- 批准号:
428842-2016 - 财政年份:2017
- 资助金额:
$ 3.93万 - 项目类别:
Industrial Research Chairs
Fast and accurate biophotonic simulations for photodynamic cancer therapy treatment planning
快速准确的生物光子模拟用于光动力癌症治疗计划
- 批准号:
490784-2015 - 财政年份:2017
- 资助金额:
$ 3.93万 - 项目类别:
Collaborative Research and Development Grants
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