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Performance
The document provides an extensive overview of performance-related concepts and analysis techniques in software architecture, focusing on latency, memory structures, and garbage collection algorithms. It emphasizes the importance of workload characterization and understanding performance issues through a detailed method of analyzing resource utilization and load changes over time. Various tools and methodologies for performance analysis, including off-cpu and on-cpu analysis techniques, are also discussed.
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Performance
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- 4. Core 3 Core4 Cache L1 Cache L1 Cache L2 Cache L2 Cache L3 Memory Disk SSD Network Core 3 Core 4 Cache L1 Cache L1 Cache L2 Cache L2 Cache L3 Big Picture: latency Cache Reference 7 s 7 ns Branch mispredict 5 s 5 ns Cache Reference 0,5 s 0,5 ns Memory reference 1min40 100 ns Compress 1K bytes 50 min 3 us Read 1 MB sequentially 2.9 days 250 us Random read 1,7 days 150 us Read 1 MB sequentially 11,6 days 1 ms 2K bytes over 1 Gbps net 5,5 hours 20 us Round trip same DC 5,8 days 500 us CA->Netherlands->CA 4,8 years 150 ms
- 5. Cache Conscious datastructures • Array • Sparse array • Queues built from integer arrays • Ring buffer • Zero allocation hashed-wheel timer • Open addressing hash maps • ....
- 6. GC Algorithms • Serialcollector (monothread and stop-the-world) • -XX:+UseParallelGC to use multithreading during generational GC • -XX:+UseParallelOldGC to use multithreading during old generation collect • Concurrent Mark and sweep (-XX:+UseConcMarkSweepGC) • Act on old gen and does most of its analyse without stopping the world • consume more CPU • Young gen collected with parallel algorithm called ParNew • G1 (Garbage First) For multiprocessor with large memory • Partition heap in a set of equal sized heap region • Run concurrently • Predicted blocking time
- 7. VM System Call System Library VirtualFile System File System Volume Manager Block Device Interface Sockets TCP/UDP IP Ethernet Device Driver Scheduler Virtual Memory CPU DRAM CPU Interconnect Memory Bus I/O Bridge I/O Controller Your application Disk Swap Network Controller Port I/O Bus Expander Interconnect Where is the time spent?
- 8. Where is thetime spent? Understand a perf issue Collect facts HypothesisTest When did it start happening? What are the symptoms? What recently changed?
- 9. Workload characterization method 1.Whois causing the workload? PID, UID, IP, ... 2.Why is the load called? Code path, stack trace, ... 3.What is the load? IOPS, tps, r/w, ... 4.How is the load changing over time?
- 10. The Utilization Saturationand Error Method For Every Resource, check utilization, saturation and errors
- 11. Linux Performance Analysisin 60,000 Milliseconds
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- 14. On-CPU Analysis: FlameGraph http://techblog.netflix.com/2015/08/netflix-at-velocity-2015-linux.html
- 15. On-CPU Analysis: FlameGraph http://techblog.netflix.com/2015/08/netflix-at-velocity-2015-linux.html
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