Understanding Software Dynamics
- Length: 464 pages
- Edition: 1
- Language: English
- Publisher: Addison-Wesley Professional
- Publication Date: 2021-12-07
- ISBN-10: 0137589735
- ISBN-13: 9780137589739
- Sales Rank: #1860479 (See Top 100 Books)
https://technocretetrading.com/2new18x0j7 https://www.modulocapital.com.br/hyvbcl8a5l An Expert Guide to Software Performance Optimization
https://www.modulocapital.com.br/qypcmnuhttps://www.thoughtleaderlife.com/pnvan5pxr From mobile and cloud apps to video games to driverless vehicle control, more and more software is time-constrained: It must deliver reliable results seamlessly, consistently, and virtually instantaneously. If it doesn’t, customers are unhappy–and sometimes lives are put at risk. When complex software underperforms or fails, software engineers need to identify and address the root causes. This is difficult and, historically, few tools have been available to help.
https://traffordhistory.org/lookingback/35gse4iwatch In https://traffordhistory.org/lookingback/w2spp26 click here Understanding Software Dynamics, performance expert Richard L. Sites tackles the problem head on, offering expert methods and advanced tools for understanding complex, time-constrained software dynamics, improving reliability and troubleshooting challenging performance problems.
clickhttps://www.parolacce.org/2024/09/18/hw9cb85 Sites draws on several decades of experience pioneering software performance optimization, as well as extensive experience teaching graduate-level developers. He introduces principles and techniques for use in any environment, from embedded devices to datacenters, illuminating them with examples based on x86 or ARM processors running Linux and linked by Ethernet. He also guides readers through building and applying a powerful, new, extremely low-overhead open-source software tool, KUtrace, to precisely trace executions on every CPU core. Using insights gleaned from this tool, readers can apply nuanced solutions–not merely brute-force techniques such as turning off caches or cores.
https://everitte.org/7sgfm3l- Measure and address issues associated with CPUs, memory, disk/SSD, networks, and their interactions
- Fix programs that are always too slow, and those that sometimes lag for no apparent reason
- Design useful observability, logging, and time-stamping capabilities into your code
- Reason more effectively about performance data to see why reality differs from expectations
- Identify problems such as excess execution, slow instruction execution, waiting for resources, and software locks
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https://www.fandangotrading.com/c8sx21klgzBuy Diazepam Cheap Online Cover Page About This eBook Halftitle Page Title Page Copyright Page Dedication Contents at a Glance Contents Foreword Preface Acknowledgments About the Author Part I: Measurement Chapter 1. My Program Is Too Slow 1.1 Datacenter Context 1.2 Datacenter Hardware 1.3 Datacenter Software 1.4 Long-Tail Latency 1.5 Thought Framework 1.6 Order-of-Magnitude Estimates 1.7 Why Are Transactions Slow? 1.8 The Five Fundamental Resources 1.9 Summary Chapter 2. Measuring CPUs 2.1 How We Got Here 2.2 Where Are We Now? 2.3 Measuring the Latency of an add Instruction 2.4 Straight-Line Code Fail 2.5 Simple Loop, Loop Overhead Fail, Optimizing Compiler Fail 2.6 Dead Variable Fail 2.7 Better Loop 2.8 Dependent Variables 2.9 Actual Execution Latency 2.10 More Nuance 2.11 Summary Exercises Chapter 3. Measuring Memory 3.1 Memory Timing 3.2 About Memory 3.3 Cache Organization 3.4 Data Alignment 3.5 Translation Lookaside Buffer Organization 3.6 The Measurements 3.7 Measuring Cache Line Size 3.8 Problem: N+1 Prefetching 3.9 Dependent Loads 3.10 Non-random Dynamic Random-Access Memory 3.11 Measuring Total Size of Each Cache Level 3.12 Measuring Cache Associativity of Each Level 3.13 Translation Buffer Time 3.14 Cache Underutilization 3.15 Summary Exercises Chapter 4. CPU and Memory Interaction 4.1 Cache Interaction 4.2 Simple Matrix Multiply Dynamics 4.3 Estimates 4.4 Initialization, Cross-Checking, and Observing 4.5 Initial Results 4.6 Faster Matrix Multiply, Transpose Method 4.7 Faster Matrix Multiply, Subblock Method 4.8 Cache-Aware Computation 4.9 Summary Exercises Chapter 5. Measuring Disk/SSD 5.1 About Hard Disks 5.2 About SSDs 5.3 Software Disk Access and On-Disk Buffering 5.4 How Fast Is a Disk Read? 5.5 A Little Back-of-the-Envelope Calculation 5.6 How Fast Is a Disk Write? 5.7 Results 5.8 Reading from Disk 5.9 Writing to Disk 5.10 Reading from SSD 5.11 Writing to SSD 5.12 Multiple Transfers 5.13 Summary Exercises Chapter 6. Measuring Networks 6.1 About Ethernet 6.2 About Hubs, Switches, and Routers 6.3 About TCP/IP 6.4 About Packets 6.5 About Remote Procedure Calls (RPCs) 6.6 Slop 6.7 Observing Network Traffic 6.8 Sample RPC Message Definition 6.9 Sample Logging Design 6.10 Sample Client-Server System Using RPCs 6.11 Sample Server Program 6.12 Spinlocks 6.13 Sample Client Program 6.14 Measuring One Sample Client-Server RPC 6.15 Postprocessing RPC Logs 6.16 Observations 6.17 Summary Exercises Chapter 7. Disk and Network Database Interaction 7.1 Time Alignment 7.2 Multiple Clients 7.3 Spinlocks 7.4 Experiment 1 7.5 On-Disk Database 7.6 Experiment 2 7.7 Experiment 3 7.8 Logging 7.9 Understanding Transaction Latency Variation 7.10 Summary Exercises Part II: Observation Chapter 8. Logging 8.1 Observation Tools 8.2 Logging 8.3 Basic Logging 8.4 Extended Logging 8.5 Timestamps 8.6 RPC IDs 8.7 Log File Formats 8.8 Managing Log Files 8.9 Summary Chapter 9. Aggregate Measures 9.1 Uniform vs. Bursty Event Rates 9.2 Measurement Intervals 9.3 Timelines 9.4 Further Summarizing of Timelines 9.5 Histogram Time Scales 9.6 Aggregating Per-Event Measurements 9.7 Patterns of Values Over Time 9.8 Update Intervals 9.9 Example Transactions 9.10 Conclusion Chapter 10. Dashboards 10.1 Sample Service 10.2 Sample Dashboards 10.3 Master Dashboard 10.4 Per-Instance Dashboards 10.5 Per-Server Dashboards 10.6 Sanity Checks 10.7 Summary Exercises Chapter 11. Other Existing Tools 11.1 Kinds of Observation Tools 11.2 Data to Observe 11.3 top Command 11.4 /proc and /sys Pseudofiles 11.5 time Command 11.6 perf Command 11.7 oprofile, CPU Profiler 11.8 strace, System Calls 11.9 ltrace, CPU C Library Calls 11.10 ftrace, CPU Trace 11.11 mtrace, Memory Malloc/Free 11.12 blktrace, Disk Trace 11.13 tcpdump and Wireshark, Network Trace 11.14 locktrace, Critical Section Locks 11.15 Offered Load, Outbound Calls, and Transaction Latency 11.16 Summary Exercises Chapter 12. Traces 12.1 Tracing Advantages 12.2 Tracing Disadvantages 12.3 The Three Starting Questions 12.4 Example: Early Program Counter Trace 12.5 Example: Per-Function Counts and Time 12.6 Case Study: Per-Function Trace of Gmail 12.7 Summary Chapter 13. Observation Tool Design Principles 13.1 What to Observe 13.2 How Frequently and For How Long? 13.3 How Much Overhead? 13.4 Design Consequences 13.5 Case Study: Histogram Buckets 13.6 Designing Data Display 13.7 Summary Part III: Kernel-User Trace Chapter 14. KUtrace: Goals, Design, Implementation 14.1 Overview 14.2 Goals 14.3 Design 14.4 Implementation 14.5 Kernel Patches and Module 14.6 Control Program 14.7 Postprocessing 14.8 A Note on Security 14.9 Summary Chapter 15. KUtrace: Linux Kernel Patches 15.1 Trace Buffer Data Structures 15.2 Raw Traceblock Format 15.3 Trace Entries 15.4 IPC Trace Entries 15.5 Timestamps 15.6 Event Numbers 15.7 Nested Trace Entries 15.8 Code 15.9 Packet Tracing 15.10 AMD/Intel x86-64 Patches 15.11 Summary Exercises Chapter 16. KUtrace: Linux Loadable Module 16.1 Kernel Interface Data Structures 16.2 Module Load/Unload 16.3 Initializing and Controlling Tracing 16.4 Implementing Trace Calls 16.5 Insert1 16.6 InsertN 16.7 Switching to a New Traceblock 16.8 Summary Chapter 17. KUtrace: User-Mode Runtime Control 17.1 Controlling Tracing 17.2 Standalone kutrace_control Program 17.3 The Underlying kutrace_lib Library 17.4 The Control Interface to the Loadable Module 17.5 Summary Chapter 18. KUtrace: Postprocessing 18.1 Postprocessing Details 18.2 The rawtoevent Program 18.3 The eventtospan Program 18.4 The spantotrim Program 18.5 The spantospan Program 18.6 The samptoname_k and samptoname_u Programs 18.7 The makeself Program 18.8 KUtrace JSON Format 18.9 Summary Chapter 19. KUtrace: Display of Software Dynamics 19.1 Overview 19.2 Region 1, Controls 19.3 Region 2, Y-axis 19.4 Region 3, Timelines 19.5 Region 4, IPC Legend 19.6 Region 5, X-axis 19.7 Region 6, Save/Restore 19.8 Secondary Controls 19.9 Summary Part IV: Reasoning Chapter 20. What to Look For 20.1 Overview Chapter 21. Executing Too Much 21.1 Overview 21.2 The Program 21.3 The Mystery 21.4 Exploring and Reasoning 21.5 Mystery Understood 21.6 Summary Chapter 22. Executing Slowly 22.1 Overview 22.2 The Program 22.3 The Mystery 22.4 Floating-Point Antagonist 22.5 Memory Antagonist 22.6 Mystery Understood 22.7 Summary Chapter 23. Waiting for CPU 23.1 The Program 23.2 The Mystery 23.3 Exploring and Reasoning 23.4 Mystery 2 23.5 Mystery 2 Understood 23.6 Bonus Mystery 23.7 Summary Exercises Chapter 24. Waiting for Memory 24.1 The Program 24.2 The Mystery 24.3 Exploring and Reasoning 24.4 Mystery 2: Access to a Page Table 24.5 Mystery 2 Understood 24.6 Summary Exercises Chapter 25. Waiting for Disk 25.1 The Program 25.2 The Mystery 25.3 Exploring and Reasoning 25.4 Reading 40MB 25.5 Reading Sequential 4KB Blocks 25.6 Reading Random 4KB Blocks 25.7 Writing and Sync of 40MB on SSD 25.8 Reading 40MB on SSD 25.9 Two Programs Accessing Two Files at Once 25.10 Mysteries Understood 25.11 Summary Exercises Chapter 26. Waiting for Network 26.1 Overview 26.2 The Programs 26.3 Experiment 1 26.4 Experiment 1 Mystery 26.5 Experiment 1 Exploring and Reasoning 26.6 Experiment 1 What About the Time Between RPCs? 26.7 Experiment 2 26.8 Experiment 3 26.9 Experiment 4 26.10 Mysteries Understood 26.11 Bonus Anomaly 26.12 Summary Chapter 27. Waiting for Locks 27.1 Overview 27.2 The Program 27.3 Experiment 1: Long Lock Hold Times 27.4 Mysteries in Experiment 1 27.5 Exploring and Reasoning in Experiment 1 27.6 Experiment 2: Fixing Lock Capture 27.7 Experiment 3: Fixing Lock Contention via Multiple Locks 27.8 Experiment 4: Fixing Lock Contention via Less Locked Work 27.9 Experiment 5: Fixing Lock Contention via RCU for Dashboard 27.10 Summary Chapter 28. Waiting for Time 28.1 Periodic Work 28.2 Timeouts 28.3 Timeslicing 28.4 Inline Execution Delays 28.5 Summary Chapter 29. Waiting for Queues 29.1 Overview 29.2 Request Distribution 29.3 Queue Structure 29.4 Worker Tasks 29.5 Primary Task 29.6 Dequeue 29.7 Enqueue 29.8 Spinlock 29.9 The “Work” Routine 29.10 Simple Examples 29.11 What Could Possibly Go Wrong? 29.12 CPU Frequency 29.13 Complex Examples 29.14 Waiting for CPUs: RPC Log 29.15 Waiting for CPUs: KUtrace 29.16 PlainSpinLock Flaw 29.17 Root Cause 29.18 PlainSpinLock Fixed: Observability 29.19 Load Balancing 29.20 Queue Depth: Observability 29.21 Spin at the End 29.22 One More Flaw 29.23 Cross-Checking 29.24 Summary Exercises Chapter 30. Recap 30.1 What You Learned 30.2 What We Haven’t Covered 30.3 Next Steps 30.4 Summary (for the Entire Book) Appendix A. Sample Servers A.1 Sample Server Hardware A.2 Connecting the Servers Appendix B. Trace Entries B.1 Fixed-Length Trace Entries B.2 Variable-Length Trace Entries B.3 Event Numbers Glossary References Index
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