“Simulating a $2M Commercial Server on a $2K PC”

1. “Simulating a $2M Commercial Server on a $2K PC” AlaaAladmeldeen, Milo Martin, Carl Mauer, Kevin Moore, Min Xu, Daniel Sorin, Mark Hill and David Wood • Computer Sciences Department, University of Wisconsin-Madison & Department of Electrical and Computer Engineering, Duke University Presented by Deepak Srinivasan

2. Motivation • DBMS and web servers areCommercial Workloads, which are growing in popularity • Lots of services rely on them, and thus it’s important to validate • Validate • Execution-based simulator • Hardware Prototypes • Analytic Models • Getting multi-million dollar multi-processor servers is probably too high a price tag for research groups testing workloads

3. Details • Trying to test simulation on a $2000 PC instead • 1st Goal: Good approximation of workloads • Scaling and fine tuning benchmarks which led to the Wisconsin Commercial Workload Suite • Online Transaction Processing (OLTP), Java Middleware, Static Web Content Server, Dynamic Web Content Server • Made several improvements in OLTP to improve its performance (12x improved) • Allowed for smaller PC to have similar throughput to that of the servers

4. More Details • 2nd Goal: Reasonable Simulation Times • Cutting Down Warm-Up Times – SIMICS and Checkpoints • Measurement Interval and How to Determine Performance – Cycles/Transaction • Short Simulation Variability – Average Multiple Trials with Random Memory Latency Times

5. Even More Details • 3rd Goal: Having Enough Timing Detail • Hard to Simulate for Multiprocessor chips – Need to Simulate every piece of Architecture • Extending SIMICS with 2 Timing Simulators • Memory Simulator – Time-consuming Components are simulated exactly, others are approximated • Detailed Processor Timing – Timing-First Simulation – Implemented with Timing and a Functional Simulator

6. Evaluation – Case Study Bash

7. Conclusions • Adapting Simulators usually used in commercial servers for small PCs is hard but possible • Ran into several difficulties including: • Scaling the Workloads while keeping them similar • Measuring Performance for a Multiprocessor System • Keeping Appropriate Timing Detail • The need to look at the Most Relevant workloads

8. Questions • Is this evaluation technique all that credible without showing a comparison between the real benchmarks running compared to these condensed single PC simulations? • Is using a small set of 4 benchmarks in the Wisconsin Commercial Workload Suite enough? • Could Cloud Computing and cheap clusters be used as an alternative to this small PC simulation approach? Which approach you think research groups would prefer?