Simulating a $2M Commercial Server on a $2K PC Alaa R. Alameldeen, Milo M.K. Martin, Carl J. Mauer, Kevin E. Moore, Min Xu, Daniel J. Sorin, Mark D. Hill and David A. Wood IEEE Computer – November 22, 2002

Commercial Workloads Business and Communication Infrastructure –DBMS –Web Servers Designed to run on High End Servers –TPC-C leader 128 Processors, 256 GB RAM, 29 TB Disk, $13M 100M Transactions in 25min warm-up + 2h Simulation on Standard PC 1-2 Processors, 1GB RAM, 120GB Disk, $2K

Simulation of Commercial Workloads Challenges –Size of Workload –Running Time –Requires Full System Simulation Highly dependent on OS, I/O Goals –Representative Approximation –Tractable Simulation Times –Sufficient Level of Detail

Wisconsin Commercial Workload Suite Online Transaction Processing (OLTP) –DB2 with TPC-C like workload SPECjbb –3-tier Java-based Middleware Static Web Content: Apache –SURGE generated requests Dynamic Web Content Serving: Slashcode –OpenSource dynamic web message posting –Perl, Apache, MySQL

Workload Scaling and Tuning Tuning of all workloads on real MP-Server –TPC-C on Sun E CPUs (167Mhz), 2GB RAM Disk images of real system used for Sim –Allows Validation of Results –Faster Benchmark Setup Initial Setup 10 Warehouses, 100MB each –Lower Throughput than expected

TPC-C Tuning Kernel and Database Configuration –Kernel limits on number of threads, semaphores, etc. –DB on raw disk Multiple Disks –DB spread over 5 disks Table Contention Reduction –More and smaller warehouses Same total DB size –Against TPC-C rule Size per warehouse is fixed

TPC-C Tuning Additional Concurrency –Number of simulated clients increased from 24 to 96 –No think or keying times Overall –Throughput increased by factor 12 Close to published results –More representative of real OLTP workload

OLTP Throughput

Workload Runtime Simulation slow-down around –Full TPC-C run (2h real) infeasible Long warm-up periods Short Simulation introduces high variability

Simulation Improvements Starting with Warm Workloads –Start from snapshot of warmed-up system Fixed Transaction Count –Simulate fixed number of transactions –Applications must notify simulator, when transactions complete

Variability Simulation executes 1 deterministic path –Path could favor certain configurations Average over multiple short simulation runs –Introduce artificial variability in memory access times Can run multiple short simulations in parallel –Preferable to one long simulation run

Timing Simulation Complex for full system simulation –Functional Simulation with Simics –Timing Simulation with 2 additional Sims CPU Timing Memory Timing Timing-First Simulation –Timing Simulator Controls when functional simulator can advance Solves races Validates functional simulator –Average Timing Error < 0.001%

Conclusion Commercial Workloads are essential for MP design –Biggest Market for MP systems Simulation on low-cost PC is hard Wisconsin Commercial Workload Suite approximates behaviour

Questions If TPC-C has to run 2h for official results, how reliable is an average over a couple of seconds? Should disk timing be simulated?