Performance and Environment Monitoring for Continuous Program Optimization

Transcription

1 IBM T.J. Watson Research Center Performance and Environment Monitoring for Continuous Program Optimization Evelyn Duesterwald Joint work with R. Azimi, C. Cascaval, M. Hauswirth, K. Sudeep, P. F. Sweeney, G. K. Tse, R. W. Wisniewski

2 How to Sustain the Application Performance Growth Curve? Performance gains from technology advances are diminishing Complexity of the SW deployment stack is increasing Execution layers can no longer be optimized in isolation Need a new methodology for application performance delivery: Tune entire application deployment stack on-site and ondemand Vertical integration Application App Server JVM O/S Hypervisor Hardware Application deployment stack Continuous and adaptive 2 PERCS Continuous Program Optimization September 16, 2004

3 Continuous Program Optimization (CPO) through Performance & Environment Monitoring () Continuous Program Optimization (CPO) increases programmer productivity by automating the laborious and challenging performance tuning effort CPO aims at tuning application by optimally adapting the application to its behavior and environment adapting environment resources to application behavior CPO is made possible through continuous whole-system Performance and Environment Monitoring () Tune & adapt (CPO) Monitor & evaluate () Continuous optimization loop 3 PERCS Continuous Program Optimization September 16, 2004

4 A Catalogue of CPO Scenarios Adapting applications to execution behavior and environment Library Tuning Adaptive MPI tuning Tuning Just-In-Time (JIT) compiler heuristics Interactive tuning environment to support algorithmic tuning Adapting the execution environment to the application s needs: Tuning the Virtual Machine (heap size, GC policies) Tuning the operating environment/os (adaptive page size, adaptive file cache management (FCM)) 4 PERCS Continuous Program Optimization September 16, 2004

5 CPO Architecture 2 Components to implement CPO scenarios: : Vertical Performance and Environment Monitoring Implements programmable monitoring functionality across execution layers Provides integrated whole system view CPO Agent (Specific to CPO scenario) programs to provide desired monitoring information Implements specific scenario optimization There may be several CPO Agents active in the system, interconnected through Application App Server Operating System Hardware Java VM Hypervisor CPO Agent control performance knob negotiate knob 5 PERCS Continuous Program Optimization September 16, 2004

6 Performance & Environment Monitoring () Flexible monitoring infrastructure to integrate monitors across execution layers Platform-independent API (API) to program CPO Agents CPO Agent for offline event tracing and logging CPO Agent for implementing CPO scenarios Designed to serve as integral part of CPO as well as stand-alone tool set Application App Server Java VM Operating System CPO Agent Event Trace Trace Visualizer Hypervisor Hardware 6 PERCS Continuous Program Optimization September 16, 2004

7 Infrastructure 1) Language-independent specification of events and their semantics 1 2 XML Event specification Tools 2) Generate language-specific event data structures and header files (Java, C, C++, Fortran) to support Layer instrumentation library CPO agent 3) implementation with a platformindependent API Application Virtual Machine O/S CPO Agent Hardware/Simulator Library 3 trace PE2 Visualizer 7 PERCS Continuous Program Optimization September 16, 2004

8 Exploratory Monitoring with Dual-path Tool Set 1) Hardware Path Java Apps JVM Native Apps Operating System (K42) CPO Agent Explore application performance and identify performance problems Hardware (GP-UL) Trace PE2 Trace Visualizer Java Apps JVM Native Apps Operating System (K42) H/W Simulator (Mambo) CPO Agent 1) Simulator Path to explore Performance effects of different solutions New hardware New monitoring functionality New events 8 PERCS Continuous Program Optimization September 16, 2004

9 on a Commercial AIX Stack Integrate existing tracing support (e.g., AIX Trace) into monitoring by intercepting existing tracing stream with wrappers Java App WebSphere JVM (J9) J9 Hook function API event record API event record API event record Trace AIX Hypervisor AIX Trace wrapper H/W 9 PERCS Continuous Program Optimization September 16, 2004

10 Demo Exploring the Performance Impact of Large Pages Preliminary Work for building a CPO Agent for Adaptive Page Sizing Vertical Event Traces: App layer: phase markers O/S layer: page faults Hardware layer: PMU counters XML event format Tool Scripts umt2k (scientific,fortran/c) K42 GP-UL client umt2k traces PE2 Visualizer 10 PERCS Continuous Program Optimization September 16, 2004

11 Complete run of umt2 (initial configuration with 4K pages) 11 PERCS Continuous Program Optimization September 16, 2004

12 Zoom into innermost loop 12 PERCS Continuous Program Optimization September 16, 2004

13 Application instrumentation to trace phase marker events 13 PERCS Continuous Program Optimization September 16, 2004

14 Complete run across OS and H/W metrics (4k pages) 14 PERCS Continuous Program Optimization September 16, 2004

15 Blue 4k pages Brown - Initial large 16M page mapping: map data structures of inner loop to large pages (each aligned at large page boundary) 15 PERCS Continuous Program Optimization September 16, 2004

16 Blue 4k pages Brown Initial Large Page Mapping: each structure aligned at large page boundary Red - Optimized large page mapping: Offset each data structure to avoid conflicts 16 PERCS Continuous Program Optimization September 16, 2004

17 Demo Summary 200.0% 150.0% 100.0% 50.0% 0.0% time page faults TLB data ERAT L1 data small page large page large page opt 17 PERCS Continuous Program Optimization September 16, 2004

18 Conclusions CPO aims at automatically tuning performance by cross-layer adaptation of code and environment global vertical monitoring infrastructure Integral part of CPO CPO scenarios are implemented as CPO Agents across the execution stack Stand-alone Tool Set A CPO Agent for vertical performance exploration and visualization Explore application behavior Hardware-Software Co-design Explore effect of new hardware on application performance Explore new monitoring functionality 18 PERCS Continuous Program Optimization September 16, 2004