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Application Slowdown Model

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Presentation on theme: "Application Slowdown Model"— Presentation transcript:

1 Application Slowdown Model
Quantifying and Controlling Impact of Interference at Shared Caches and Main Memory Lavanya Subramanian, Vivek Seshadri, Arnab Ghosh, Samira Khan, Onur Mutlu

2 Problem: Interference at Shared Resources
Core Core Shared Cache Main Memory Core Core 1. High application slowdowns 2. Unpredictable application slowdowns

3 Problem: Interference at Shared Resources
Core Core Shared Cache Main Memory Core Core Our Goal: Achieve high and predictable performance

4 Our Approach Build a model to accurately estimate slowdowns
Use slowdown estimates to build slowdown-aware resource management mechanisms

5 Challenge in Estimating Slowdown
Slowdown= Performance Alone Performance Shared lowdown of an application is its performance when it is run stand alone on a system to its performance when it is sharing the system with other applications. An application’s performance when it is sharing the system with other applications can be measured in a straightforward manner. However, measuring an application’s alone performance, without actually running it alone is harder. This is where are first observation comes in.

6 Challenge in Estimating Slowdown
Slowdown= Performance Alone Performance Shared Slowdown of an application is its performance when it is run stand alone on a system to its performance when it is sharing the system with other applications. An application’s performance when it is sharing the system with other applications can be measured in a straightforward manner. However, measuring an application’s alone performance, without actually running it alone is harder. This is where are first observation comes in. Easy

7 Challenge in Estimating Slowdown
Slowdown= Performance Alone Performance Shared Slowdown of an application is its performance when it is run stand alone on a system to its performance when it is sharing the system with other applications. An application’s performance when it is sharing the system with other applications can be measured in a straightforward manner. However, measuring an application’s alone performance, without actually running it alone is harder. This is where are first observation comes in. Easy

8 Our estimation error: 10%
Our Model Our model overcomes this challenge Our estimation error: 10% Best previous model’s error: 30% Slowdown of an application is its performance when it is run stand alone on a system to its performance when it is sharing the system with other applications. An application’s performance when it is sharing the system with other applications can be measured in a straightforward manner. However, measuring an application’s alone performance, without actually running it alone is harder. This is where are first observation comes in.

9 Leveraging Our Slowdown Estimates

10 Leveraging Our Slowdown Estimates
Core Shared Cache Main Memory Core Slowdown-aware cache capacity partitioning

11 Leveraging Our Slowdown Estimates
Core Shared Cache Main Memory Core Slowdown-aware memory bandwidth partitioning

12 Talk at 2:40pm in Tapa Ballroom 2 Application Slowdown Model
Lavanya Subramanian, Vivek Seshadri, Arnab Ghosh, Samira Khan, Onur Mutlu

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