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Scalable Tools for Non-Intrusive Performance Debugging of Parallel Linux Workloads
Scalable Tools for Non-Intrusive Performance Debugging of Parallel Linux Workloads Robert Schöne∗ Joseph Schuchart∗ Thomas Ilsche∗ Daniel Hackenberg∗ ∗ZIH, Technische Universität Dresden {robert.schoene|joseph.schuchart|thomas.ilsche|daniel.hackenberg}@tu-dresden.de Abstract for extending battery life in mobile devices or to en- sure maximum ROI of servers in production environ- ments. However, performance tuning is still a complex There are a variety of tools to measure the performance task that often requires specialized tools to gain insight of Linux systems and the applications running on them. into the behavior of applications. Today there are only However, the resulting performance data is often pre- a small number of tools available to developers for un- sented in plain text format or only with a very basic user derstanding the run-time performance characteristics of interface. For large systems with many cores and con- their code, both on the kernel and the user land side. current threads, it is increasingly difficult to present the Moreover, the increasing parallelism of modern multi- data in a clear way for analysis. Moreover, certain per- and many-core processors creates an additional chal- formance analysis and debugging tasks require the use lenge since scalability is usually not a major focus of of a high-resolution time-line based approach, again en- standard performance analysis tools. In contrast, scal- tailing data visualization challenges. Tools in the area ability of applications and performance analysis tools of High Performance Computing (HPC) have long been have long been topics in the High Performance Com- able to scale to hundreds or thousands of parallel threads puting (HPC) community. -
Verification of Formal Requirements Through Tracing
DEGREE PROJECT IN INFORMATION AND COMMUNICATION TECHNOLOGY, SECOND CYCLE, 30 CREDITS STOCKHOLM, SWEDEN 2020 Verification of Formal Requirements through Tracing JORRIT J. OLTHUIS KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCE ABSTRACT I Abstract Software development in the railway application is governed by strict stan- dards which aim to ensure safety. It is for example highly recommended to use formal methods when specifying requirements. Moreover, it is mandatory to have certain roles be fulfilled by different people. A common technique is developing software tests for the requirements. Mak- ing sure that software requirements are properly described, interpreted and implemented by different people is a major challenge. Tests fully depend on the tester to cover all scenarios. Having more methods that simplify require- ment tracing and that depends less on thoroughness of the tester would provide many benefits. This thesis investigates whether and how software tracing can be used to vali- date formal requirements of software. The goal is to perform trace validation such that it can be used to complement more traditional verification techniques. By verifying formal requirements on traces, the detection of errors depends on the events in the traces. As a consequence, more traces provide a higher chance of detecting errors. Thereby eliminating risk of the tester missing important cases. The presented verification approach firstly specifies requirements in lin- ear temporal logic and converts this specification to a non-deterministic Büchi automaton, or a finite state machine which is also evaluated. Secondly, the approach describes several alternatives for collecting traces and how to link those to the formal specification. -
Tracing Tools
Tracing Tools Michal Seklet´ar [email protected] March 21, 2019 whoami Senior Software Engineer RHEL systemd maintainer SW engineer interested in tracing and debugging Michal Seklet´ar [email protected] Tracing Tools March 21, 2019 2 / 38 Motivation Have you ever wanted to answer questions like, What files in /etc are being accessed on the system ? How big are memory allocations done by [DAEMON] (insert you favorite) ? What process is a source of slow filesystem operations (e.g. slower than 50 ms) ? Michal Seklet´ar [email protected] Tracing Tools March 21, 2019 3 / 38 Agenda PART I { Introduction Tracing vs. Debugging Goals Methodology PART II { Tools strace and ltrace (ptrace) trace-cmd (ftrace) SystemTap (kprobes) bcc-tools (eBPF) PART III { Exercises Michal Seklet´ar [email protected] Tracing Tools March 21, 2019 4 / 38 PART I { Introduction Michal Seklet´ar [email protected] Tracing Tools March 21, 2019 5 / 38 Intro { Debugging vs. Tracing Debugging The process of identifying and removing errors from computer software. Approaches Staring into the code Debug logging Debuggers gdb lldb Michal Seklet´ar [email protected] Tracing Tools March 21, 2019 6 / 38 Intro { Debugging vs. Tracing Tracing Non-intrusive observation and monitoring of a software system. Approaches Syscall monitoring Gathering execution traces Stack sampling Debug logging Michal Seklet´ar [email protected] Tracing Tools March 21, 2019 7 / 38 Intro { Goals Goals Better understanding of the system behavior Tracing should be as non-intrusive as possible In-kernel summarization (if possible) and statistical data gathering Michal Seklet´ar [email protected] Tracing Tools March 21, 2019 8 / 38 Intro { Methodology Right tool for the job What tracing tools should I use? Unfortunately, answer to this question on Linux is not straight forward. -
Red Hat Enterprise Linux 8.2 8.2 Release Notes
Red Hat Enterprise Linux 8.2 8.2 Release Notes Release Notes for Red Hat Enterprise Linux 8.2 Last Updated: 2021-08-18 Red Hat Enterprise Linux 8.2 8.2 Release Notes Release Notes for Red Hat Enterprise Linux 8.2 Legal Notice Copyright © 2021 Red Hat, Inc. The text of and illustrations in this document are licensed by Red Hat under a Creative Commons Attribution–Share Alike 3.0 Unported license ("CC-BY-SA"). An explanation of CC-BY-SA is available at http://creativecommons.org/licenses/by-sa/3.0/ . In accordance with CC-BY-SA, if you distribute this document or an adaptation of it, you must provide the URL for the original version. Red Hat, as the licensor of this document, waives the right to enforce, and agrees not to assert, Section 4d of CC-BY-SA to the fullest extent permitted by applicable law. Red Hat, Red Hat Enterprise Linux, the Shadowman logo, the Red Hat logo, JBoss, OpenShift, Fedora, the Infinity logo, and RHCE are trademarks of Red Hat, Inc., registered in the United States and other countries. Linux ® is the registered trademark of Linus Torvalds in the United States and other countries. Java ® is a registered trademark of Oracle and/or its affiliates. XFS ® is a trademark of Silicon Graphics International Corp. or its subsidiaries in the United States and/or other countries. MySQL ® is a registered trademark of MySQL AB in the United States, the European Union and other countries. Node.js ® is an official trademark of Joyent. Red Hat is not formally related to or endorsed by the official Joyent Node.js open source or commercial project. -
Linux Performance Profiling Tool
Linux Performance Profiling Tool Minsoo Ryu Real-Time Computing and Communications Lab. Hanyang University [email protected] Real-Time Computing and Communications Lab., Hanyang University http://rtcc.hanyang.ac.kr Outline Example source Profiling . Perf . Gprof . Oprofile Tracing . Strace . Ltarce . Ftrace Real-Time Computing and Communications Lab., Hanyang University http://rtcc.hanyang.ac.kr 22 Example Source Real-Time Computing and Communications Lab., Hanyang University http://rtcc.hanyang.ac.kr Example Source UDP program . Server • ./UDP_server [port] . Client1 / client2 • ./UDP_client [ip address] [port] [user name] Real-Time Computing and Communications Lab., Hanyang University http://rtcc.hanyang.ac.kr 44 Example Source Real-Time Computing and Communications Lab., Hanyang University http://rtcc.hanyang.ac.kr 55 Example Source Server Client Data Send/Receive exit Procedure of UDP Socket Programming Real-Time Computing and Communications Lab., Hanyang University http://rtcc.hanyang.ac.kr 66 Outline Example source Profiling . Perf . Gprof . Oprofile Tracing . Strace . Ltarce . Ftrace Real-Time Computing and Communications Lab., Hanyang University http://rtcc.hanyang.ac.kr 77 Profiling Real-Time Computing and Communications Lab., Hanyang University http://rtcc.hanyang.ac.kr Perf Real-Time Computing and Communications Lab., Hanyang University http://rtcc.hanyang.ac.kr Perf What is perf . Performance counters for Linux . Perf profiler collects data through a variety of techniques • Hardware interrupts, code instrumentation, instruction set simulation, operating systems, hooking, performance counters . Operates with PMU information taking the CPU helpful • The reason why user-level program is included into the kernel source • Perf is closely associated with the kernel ABI Real-Time Computing and Communications Lab., Hanyang University http://rtcc.hanyang.ac.kr 1010 Perf Perf install . -
Linux Performance Tools
Oct, 2014 Linux Performance Tools Brendan Gregg Senior Performance Architect Performance Engineering Team [email protected] @brendangregg A quick tour of many tools… • Massive AWS EC2 Linux cloud – Tens of thousands of instances – Autoscale by ~3k each day – CentOS and Ubuntu • FreeBSD for content delivery – Approx 33% of US Internet traffic at night • Performance is criRcal – Customer sasfacRon: >50M subscribers – $$$ price/performance – Develop tools for cloud-wide analysis; use server tools as needed • Just launched in Europe! Brendan Gregg • Senior Performance Architect, Ne8lix – Linux and FreeBSD performance – Performance Engineering team (@coburnw) • Recent work: – Linux perf-tools, using crace & perf_events – Systems Performance, PrenRce Hall • Previous work includes: – USE Method, flame graphs, uRlizaon & latency heat maps, DTrace tools, ZFS L2ARC • Twier @brendangregg (these slides) Agenda • Methodologies & Tools • Tool Types: – Observability • Basic • Intermediate • Advanced – Benchmarking – Tuning – Stac • Tracing Aim: to show what can be done knowing that something can be done is more important than knowing how to do it. Methodologies & Tools Methodologies & Tools • There are dozens of performance tools for Linux – Packages: sysstat, procps, coreuls, … – Commercial products • Methodologies can provide guidance for choosing and using tools effecRvely An3-Methodologies • The lack of a deliberate methodology… • Street Light AnR-Method: – 1. Pick observability tools that are • Familiar • Found on the Internet, or at random – 2. Run