Presentation is loading. Please wait.

Presentation is loading. Please wait.

CSE 591: Energy-Efficient Computing Lecture 3 SPEED: processor Anshul Gandhi 347, CS building

Published bySheena Garrett Modified over 9 years ago

Similar presentations

Presentation on theme: "CSE 591: Energy-Efficient Computing Lecture 3 SPEED: processor Anshul Gandhi 347, CS building"— Presentation transcript:

1 CSE 591: Energy-Efficient Computing Lecture 3 SPEED: processor Anshul Gandhi 347, CS building anshul@cs.stonybrook.edu

2 opt_allocation paper

3 U.S. Data Center Energy Consumption 3 $ 8.4 billion kWh (in billions)  120 billion kWh 12 billion kWh 50 billion kWh Source: EPA report to Congress on Server and Data Center Energy Efficiency,2007

4 4 P Get the best performance from the power, P, that we have. Goal Data Center

5 5 P P1P1 P2P2 P3P3 Goal How to split P to minimize mean response time? Right answer can improve performance by up to 5X Constraint: P ≥ P 1 + P 2 + P 3

6 Our Experimental Results DFS: Dynamic Frequency Scaling Power (Watts) DFS 6 Frequency (GHz) (server speed) How power affects server speed for a single server “linear” P = system power NOT processor power

7 Our Experimental Results Power (Watts) DFS 7 Frequency (GHz) How power affects server speed for a single server Power (Watts) Frequency (GHz) Power (Watts) Frequency (GHz) DVFS +DFS Power (Watts) DFS Frequency (GHz) Power (Watts) Frequency (GHz) Power (Watts) Frequency (GHz) DVFS +DFS “LINPACK” CPU BOUND “STREAM” MEM BOUND

8 Power Allocation Results 8 CPU bound “LINPACK” Memory bound “STREAM” DFS DVFS DVFS+DFS Power (Watts) DFS Frequency (GHz)

9 Power Allocation Results 9 CPU bound “LINPACK” Memory bound “STREAM” DFS DVFS DVFS+DFS Power (Watts) Frequency (GHz) DVFS

10 Power Allocation Results 10 CPU bound “LINPACK” Memory bound “STREAM” DFS DVFS DVFS+DFS Power (Watts) Frequency (GHz) DVFS +DFS

11 Power Allocation Results 11 CPU bound “LINPACK” Memory bound “STREAM” DFS DVFS DVFS+DFS DFS DVFS Arrival rate (jobs/sec) Mean Resp. Time (sec) Arrival rate (jobs/sec)

12 Conclusions: How to allocate power optimally 12 Speed Scaling? Arrival Rate? Linear, SteepLinear, FlatCubic Arrival Rate? PowMax PowMin High LowHigh Low High Low PowMax PowMed

Download ppt "CSE 591: Energy-Efficient Computing Lecture 3 SPEED: processor Anshul Gandhi 347, CS building"

Similar presentations

Energy-efficient Task Scheduling in Heterogeneous Environment 2013/10/25.

Energy-efficient Task Scheduling in Heterogeneous Environment 2013/10/25.
Zhou Peng, Zuo Decheng, Zhou Haiying Harbin Institute of Technology 1.

Zhou Peng, Zuo Decheng, Zhou Haiying Harbin Institute of Technology 1.
S YSTEM -W IDE E NERGY M ANAGEMENT FOR R EAL -T IME T ASKS : L OWER B OUND AND A PPROXIMATION Xiliang Zhong and Cheng-Zhong Xu ICCAD 2006, ACM Trans. on.

S YSTEM -W IDE E NERGY M ANAGEMENT FOR R EAL -T IME T ASKS : L OWER B OUND AND A PPROXIMATION Xiliang Zhong and Cheng-Zhong Xu ICCAD 2006, ACM Trans. on.
International Symposium on Low Power Electronics and Design Energy-Efficient Non-Minimal Path On-chip Interconnection Network for Heterogeneous Systems.

International Symposium on Low Power Electronics and Design Energy-Efficient Non-Minimal Path On-chip Interconnection Network for Heterogeneous Systems.
CSE 691: Energy-Efficient Computing Lecture 20 review Anshul Gandhi 1307, CS building

CSE 691: Energy-Efficient Computing Lecture 20 review Anshul Gandhi 1307, CS building
1 MemScale: Active Low-Power Modes for Main Memory Qingyuan Deng, David Meisner*, Luiz Ramos, Thomas F. Wenisch*, and Ricardo Bianchini Rutgers University.

1 MemScale: Active Low-Power Modes for Main Memory Qingyuan Deng, David Meisner*, Luiz Ramos, Thomas F. Wenisch*, and Ricardo Bianchini Rutgers University.
A Cyber-Physical Systems Approach to Energy Management in Data Centers Presented by Chen He Adopted form the paper authors.

A Cyber-Physical Systems Approach to Energy Management in Data Centers Presented by Chen He Adopted form the paper authors.
CSE 691: Energy-Efficient Computing Lecture 4 SCALING: stateless vs. stateful Anshul Gandhi 1307, CS building

CSE 691: Energy-Efficient Computing Lecture 4 SCALING: stateless vs. stateful Anshul Gandhi 1307, CS building
Power Cost Reduction in Distributed Data Centers Yuan Yao University of Southern California 1 Joint work: Longbo Huang, Abhishek Sharma, LeanaGolubchik.

Power Cost Reduction in Distributed Data Centers Yuan Yao University of Southern California 1 Joint work: Longbo Huang, Abhishek Sharma, LeanaGolubchik.
1 Introduction Background: CS 3810 or equivalent, based on Hennessy and Patterson’s Computer Organization and Design Text for CS/EE 6810: Hennessy and.

1 Introduction Background: CS 3810 or equivalent, based on Hennessy and Patterson’s Computer Organization and Design Text for CS/EE 6810: Hennessy and.
SLA-aware Virtual Resource Management for Cloud Infrastructures

SLA-aware Virtual Resource Management for Cloud Infrastructures
CSE 691: Energy-Efficient Computing Lecture 3 SLEEP: full-system Anshul Gandhi 1307, CS building

CSE 691: Energy-Efficient Computing Lecture 3 SLEEP: full-system Anshul Gandhi 1307, CS building
Energy, Energy, Energy  Worldwide efforts to reduce energy consumption  People can conserve. Large percentage savings possible, but each individual has.

Energy, Energy, Energy  Worldwide efforts to reduce energy consumption  People can conserve. Large percentage savings possible, but each individual has.
Synergy.cs.vt.edu Power and Performance Characterization of Computational Kernels on the GPU Yang Jiao, Heshan Lin, Pavan Balaji (ANL), Wu-chun Feng.

Synergy.cs.vt.edu Power and Performance Characterization of Computational Kernels on the GPU Yang Jiao, Heshan Lin, Pavan Balaji (ANL), Wu-chun Feng.
Task Dependence in Scheduling and Load Balancing Prof. Adam Meyerson UCLA.

Task Dependence in Scheduling and Load Balancing Prof. Adam Meyerson UCLA.
Power-Aware SoC Test Optimization through Dynamic Voltage and Frequency Scaling Vijay Sheshadri, Vishwani D. Agrawal, Prathima Agrawal Dept. of Electrical.

Power-Aware SoC Test Optimization through Dynamic Voltage and Frequency Scaling Vijay Sheshadri, Vishwani D. Agrawal, Prathima Agrawal Dept. of Electrical.
Green IT and Data Centers Darshan R. Kapadia Gregor von Laszewski 1.

Green IT and Data Centers Darshan R. Kapadia Gregor von Laszewski 1.
Folklore Confirmed: Compiling for Speed = Compiling for Energy Tomofumi Yuki INRIA, Rennes Sanjay Rajopadhye Colorado State University 1.

Folklore Confirmed: Compiling for Speed = Compiling for Energy Tomofumi Yuki INRIA, Rennes Sanjay Rajopadhye Colorado State University 1.
XI HE Computing and Information Science Rochester Institute of Technology Rochester, NY USA Rochester Institute of Technology Service.

XI HE Computing and Information Science Rochester Institute of Technology Rochester, NY USA Rochester Institute of Technology Service.
OPTIMAL SERVER PROVISIONING AND FREQUENCY ADJUSTMENT IN SERVER CLUSTERS Presented by: Xinying Zheng 09/13/2010 1 XINYING ZHENG, YU CAI MICHIGAN TECHNOLOGICAL.

OPTIMAL SERVER PROVISIONING AND FREQUENCY ADJUSTMENT IN SERVER CLUSTERS Presented by: Xinying Zheng 09/13/ XINYING ZHENG, YU CAI MICHIGAN TECHNOLOGICAL.

Similar presentations

Ads by Google