Perf Tool: Performance Analysis Tool for Linux
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STAT 625: Statistical Case Studies 1 Our Computing Environment(S)
John W. Emerson, Department of Statistics, Yale University © 2013 1 STAT 625: Statistical Case Studies John W. Emerson Yale University Abstract This term, I’ll generally present brief class notes and scripts, but much of the lecture material will simply be presented in class and/or available online. However, student participation is a large part of this course, and at any time I may call upon any of you to share some of your work. Be prepared. This won’t be a class where you sit and absorb material. I strongly encourage you to work with other students; you can learn a lot from each other. To get anything out of this course you’ll need to put in the time for the sake of learning and strengthening your skills, not for the sake of jumping through the proverbial hoop. Lesson 1: Learning how to communicate. This document was created using LATEX and Sweave (which is really an R package). There are some huge advantages to a workflow like this, relating to a topic called reproducible research. Here’s my thought: pay your dues now, reap the benefits later. Don’t trust me on everything, but trust me on this. A sister document was created using R Markdown and the markdown package, and this is also acceptable. Microsoft Office is not. So, in today’s class I’ll show you how I produced these documents and I’ll give you the required files. I recommend you figure out how to use LATEX on your own computer. You already have Sweave, because it comes with R. -
System Calls and I/O
System Calls and I/O CS 241 January 27, 2012 Copyright ©: University of Illinois CS 241 Staff 1 This lecture Goals Get you familiar with necessary basic system & I/O calls to do programming Things covered in this lecture Basic file system calls I/O calls Signals Note: we will come back later to discuss the above things at the concept level Copyright ©: University of Illinois CS 241 Staff 2 System Calls versus Function Calls? Copyright ©: University of Illinois CS 241 Staff 3 System Calls versus Function Calls Function Call Process fnCall() Caller and callee are in the same Process - Same user - Same “domain of trust” Copyright ©: University of Illinois CS 241 Staff 4 System Calls versus Function Calls Function Call System Call Process Process fnCall() sysCall() OS Caller and callee are in the same Process - Same user - OS is trusted; user is not. - Same “domain of trust” - OS has super-privileges; user does not - Must take measures to prevent abuse Copyright ©: University of Illinois CS 241 Staff 5 System Calls System Calls A request to the operating system to perform some activity System calls are expensive The system needs to perform many things before executing a system call The computer (hardware) saves its state The OS code takes control of the CPU, privileges are updated. The OS examines the call parameters The OS performs the requested function The OS saves its state (and call results) The OS returns control of the CPU to the caller Copyright ©: University of Illinois CS 241 Staff 6 Steps for Making a System Call -
Kernel Boot-Time Tracing
Kernel Boot-time Tracing Linux Plumbers Conference 2019 - Tracing Track Masami Hiramatsu <[email protected]> Linaro, Ltd. Speaker Masami Hiramatsu - Working for Linaro and Linaro members - Tech Lead for a Landing team - Maintainer of Kprobes and related tracing features/tools Why Kernel Boot-time Tracing? Debug and analyze boot time errors and performance issues - Measure performance statistics of kernel boot - Analyze driver init failure - Debug boot up process - Continuously tracing from boot time etc. What We Have There are already many ftrace options on kernel command line ● Setup options (trace_options=) ● Output to printk (tp_printk) ● Enable events (trace_events=) ● Enable tracers (ftrace=) ● Filtering (ftrace_filter=,ftrace_notrace=,ftrace_graph_filter=,ftrace_graph_notrace=) ● Add kprobe events (kprobe_events=) ● And other options (alloc_snapshot, traceoff_on_warning, ...) See Documentation/admin-guide/kernel-parameters.txt Example of Kernel Cmdline Parameters In grub.conf linux /boot/vmlinuz-5.1 root=UUID=5a026bbb-6a58-4c23-9814-5b1c99b82338 ro quiet splash tp_printk trace_options=”sym-addr” trace_clock=global ftrace_dump_on_oops trace_buf_size=1M trace_event=”initcall:*,irq:*,exceptions:*” kprobe_event=”p:kprobes/myevent foofunction $arg1 $arg2;p:kprobes/myevent2 barfunction %ax” What Issues? Size limitation ● kernel cmdline size is small (< 256bytes) ● A half of the cmdline is used for normal boot Only partial features supported ● ftrace has too complex features for single command line ● per-event filters/actions, instances, histograms. Solutions? 1. Use initramfs - Too late for kernel boot time tracing 2. Expand kernel cmdline - It is not easy to write down complex tracing options on bootloader (Single line options is too simple) 3. Reuse structured boot time data (Devicetree) - Well documented, structured data -> V1 & V2 series based on this. Boot-time Trace: V1 and V2 series V1 and V2 series posted at June. -
Linux Perf Event Features and Overhead
Linux perf event Features and Overhead 2013 FastPath Workshop Vince Weaver http://www.eece.maine.edu/∼vweaver [email protected] 21 April 2013 Performance Counters and Workload Optimized Systems • With processor speeds constant, cannot depend on Moore's Law to deliver increased performance • Code analysis and optimization can provide speedups in existing code on existing hardware • Systems with a single workload are best target for cross- stack hardware/kernel/application optimization • Hardware performance counters are the perfect tool for this type of optimization 1 Some Uses of Performance Counters • Traditional analysis and optimization • Finding architectural reasons for slowdown • Validating Simulators • Auto-tuning • Operating System optimization • Estimating power/energy in software 2 Linux and Performance Counters • Linux has become the operating system of choice in many domains • Runs most of the Top500 list (over 90%) on down to embedded devices (Android Phones) • Until recently had no easy access to hardware performance counters, limiting code analysis and optimization. 3 Linux Performance Counter History • oprofile { system-wide sampling profiler since 2002 • perfctr { widely used general interface available since 1999, required patching kernel • perfmon2 { another general interface, included in kernel for itanium, made generic, big push for kernel inclusion 4 Linux perf event • Developed in response to perfmon2 by Molnar and Gleixner in 2009 • Merged in 2.6.31 as \PCL" • Unusual design pushes most functionality into kernel -
Lab #6: Stat Overview Stat
February 17, 2017 CSC 357 1 Lab #6: Stat Overview The purpose of this lab is for you to retrieve from the filesystem information pertaining to specified files. You will use portions of this lab in Assignment #4, so be sure to write code that can be reused. stat Write a simplified version of the stat utility available on some Unix distributions. This program should take any number of file names as command-line arguments and output information pertaining to each file as described below (you should use the stat system call). The output from your program should look as follows: File: ‘Makefile’ Type: Regular File Size: 214 Inode: 4702722 Links: 1 Access: -rw------- The stat system call provides more information about a file, but this lab only requires the above. The format of each field follows: • File: the name of the file being examined. • Type: the type of file output as “Regular File”, “Directory”, “Character Device”, “Block Device”, “FIFO”, or “Symbolic Link” • Size: the number of bytes in the file. • Inode: the file’s inode. • Links: the number of links to the file. • Access: the access permissions for the file. This field is the most involved since the output string can take many forms. The first bit of the access permissions denotes the type (similar to the second field above). The valid characters for the first bit are: b – Block special file. c – Character special file. d – Directory. l – Symbolic link. p – FIFO. - – Regular file. The remaining bits denote the read, write and execute permissions for the user, group, and others. -
Developer Guide
Red Hat Enterprise Linux 6 Developer Guide An introduction to application development tools in Red Hat Enterprise Linux 6 Last Updated: 2017-10-20 Red Hat Enterprise Linux 6 Developer Guide An introduction to application development tools in Red Hat Enterprise Linux 6 Robert Krátký Red Hat Customer Content Services [email protected] Don Domingo Red Hat Customer Content Services Jacquelynn East Red Hat Customer Content Services Legal Notice Copyright © 2016 Red Hat, Inc. and others. This document is licensed by Red Hat under the Creative Commons Attribution-ShareAlike 3.0 Unported License. If you distribute this document, or a modified version of it, you must provide attribution to Red Hat, Inc. and provide a link to the original. If the document is modified, all Red Hat trademarks must be removed. 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, 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. -
Linux on IBM Z
Linux on IBM Z Pervasive Encryption with Linux on IBM Z: from a performance perspective Danijel Soldo Software Performance Analyst Linux on IBM Z Performance Evaluation _ [email protected] IBM Z / Danijel Soldo – Pervasive Encryption with Linux on IBM Z: from a performance perspective / © 2018 IBM Corporation Notices and disclaimers • © 2018 International Business Machines Corporation. No part of • Performance data contained herein was generally obtained in a this document may be reproduced or transmitted in any form controlled, isolated environments. Customer examples are without written permission from IBM. presented as illustrations of how those • U.S. Government Users Restricted Rights — use, duplication • customers have used IBM products and the results they may have or disclosure restricted by GSA ADP Schedule Contract with achieved. Actual performance, cost, savings or other results in IBM. other operating environments may vary. • Information in these presentations (including information relating • References in this document to IBM products, programs, or to products that have not yet been announced by IBM) has been services does not imply that IBM intends to make such products, reviewed for accuracy as of the date of initial publication programs or services available in all countries in which and could include unintentional technical or typographical IBM operates or does business. errors. IBM shall have no responsibility to update this information. This document is distributed “as is” without any warranty, • Workshops, sessions and associated materials may have been either express or implied. In no event, shall IBM be liable for prepared by independent session speakers, and do not necessarily any damage arising from the use of this information, reflect the views of IBM. -
Linux Performance Tools
Linux Performance Tools Brendan Gregg Senior Performance Architect Performance Engineering Team [email protected] @brendangregg This Tutorial • A tour of many Linux performance tools – To show you what can be done – With guidance for how to do it • This includes objectives, discussion, live demos – See the video of this tutorial Observability Benchmarking Tuning Stac Tuning • Massive AWS EC2 Linux cloud – 10s of thousands of cloud instances • FreeBSD for content delivery – ~33% of US Internet traffic at night • Over 50M subscribers – Recently launched in ANZ • Use Linux server tools as needed – After cloud monitoring (Atlas, etc.) and instance monitoring (Vector) tools Agenda • Methodologies • Tools • Tool Types: – Observability – Benchmarking – Tuning – Static • Profiling • Tracing Methodologies Methodologies • Objectives: – Recognize the Streetlight Anti-Method – Perform the Workload Characterization Method – Perform the USE Method – Learn how to start with the questions, before using tools – Be aware of other methodologies My system is slow… DEMO & DISCUSSION Methodologies • There are dozens of performance tools for Linux – Packages: sysstat, procps, coreutils, … – Commercial products • Methodologies can provide guidance for choosing and using tools effectively • A starting point, a process, and an ending point An#-Methodologies • The lack of a deliberate methodology… Street Light An<-Method 1. Pick observability tools that are: – Familiar – Found on the Internet – Found at random 2. Run tools 3. Look for obvious issues Drunk Man An<-Method • Tune things at random until the problem goes away Blame Someone Else An<-Method 1. Find a system or environment component you are not responsible for 2. Hypothesize that the issue is with that component 3. Redirect the issue to the responsible team 4. -
On Access Control Model of Linux Native Performance Monitoring Motivation
On access control model of Linux native performance monitoring Motivation • socialize Perf access control management to broader community • promote the management to security sensitive production environments • discover demand on extensions to the existing Perf access control model 2 Model overview • Subjects: processes • Access control: • superuser root • LSM hooks for MAC (e.g. SELinux) subjects • privileged user groups • Linux capabilities (DAC) • unprivileged users • perf_event_paranoid sysctl access and • Objects: telemetry data • Resource control: • tracepoints, OS events resource control • CPU time: sample rate & throttling • CPU • Memory: perf_events_mlock_kb sysctl • Uncore Objects • Other HW • File descriptors: ulimit -n (RLIMIT_NOFILE) system • Scope • Level user cgroups • process • user mode • cgroups • kernel kernel • system process • hypervisor hypervisor 3 Subjects Users • root, superuser: • euid = 0 and/or CAP_SYS_ADMIN • unprivileged users: • perf_event_paranoid sysctl • Perf privileged user group: -rwxr-x--- 2 root perf_users 11M Oct 19 15:12 perf # getcap perf perf = cap_perfmon,…=ep root unprivileged Perf users 4 Telemetry, scope, level Telemetr Objects: SW, HW telemetry data y Uncore • tracepoints, OS events, eBPF • CPUs events and related HW CPU • Uncore events (LLC, Interconnect, DRAM) SW events • Other (e.g. FPGA) process cgroup user Scope: Level: system kernel • process • user hypervisor • cgroups • kernel Scope Leve • system wide • hypervisor l 5 perf: interrupt took too long (3000 > 2000), lowering kernel.perf_event_max_sample_rate -
Analysing CMS Software Performance Using Igprof, Oprofile and Callgrind
Analysing CMS software performance using IgProf, OPro¯le and callgrind L Tuura1, V Innocente2, G Eulisse1 1 Northeastern University, Boston, MA, USA 2 CERN, Geneva, Switzerland Abstract. The CMS experiment at LHC has a very large body of software of its own and uses extensively software from outside the experiment. Understanding the performance of such a complex system is a very challenging task, not the least because there are extremely few developer tools capable of pro¯ling software systems of this scale, or producing useful reports. CMS has mainly used IgProf, valgrind, callgrind and OPro¯le for analysing the performance and memory usage patterns of our software. We describe the challenges, at times rather extreme ones, faced as we've analysed the performance of our software and how we've developed an understanding of the performance features. We outline the key lessons learnt so far and the actions taken to make improvements. We describe why an in-house general pro¯ler tool still ends up besting a number of renowned open-source tools, and the improvements we've made to it in the recent year. 1. The performance optimisation issue The Compact Muon Solenoid (CMS) experiment on the Large Hadron Collider at CERN [1] is expected to start running within a year. The computing requirements for the experiment are immense. For the ¯rst year of operation, 2008, we budget 32.5M SI2k (SPECint 2000) computing capacity. This corresponds to some 2650 servers if translated into the most capable computers currently available to us.1 It is critical CMS on the one hand acquires the resources needed for the planned physics analyses, and on the other hand optimises the software to complete the task with the resources available. -
Kernel Runtime Security Instrumentation Process Is Executed
Kernel Runtime Security Instrumentation KP Singh Linux Plumbers Conference Motivation Security Signals Mitigation Audit SELinux, Apparmor (LSMs) Perf seccomp Correlation with It's bad, stop it! maliciousness but do not imply it Adding a new Signal Signals Mitigation Update Audit Audit (user/kernel) SELinux, Apparmor (LSMs) to log environment Perf variables seccomp Security Signals Mitigation Audit SELinux, Apparmor (LSMs) Perf seccomp Update the mitigation logic for a malicious actor with a known LD_PRELOAD signature Signals ● A process that executes and deletes its own executable. ● A Kernel module that loads and "hides" itself ● "Suspicious" environment variables. Mitigations ● Prevent mounting of USB drives on servers. ● Dynamic whitelist of known Kernel modules. ● Prevent known vulnerable binaries from running. How does it work? Why LSM? ● Mapping to security behaviours rather than the API. ● Easy to miss if instrumenting using syscalls (eg. execve, execveat) ● Benefit the LSM ecosystem by incorporating feedback from the security community. Run my code when a Kernel Runtime Security Instrumentation process is executed /sys/kernel/security/krsi/process_execution my_bpf_prog.o (bprm_check_security) bpf [BPF_PROG_LOAD] open [O_RDWR] securityfs_fd prog_fd bpf [BPF_PROG_ATTACH] LSM:bprm_check_security (when a process is executed) KRSI's Hook Other LSM Hooks Tying it all Together Reads events from the buffer and processes them Userspace further Daemon/Agent User Space Buffer Kernel Space eBPF programs output to a buffer process_execution -
Stat System Administration Guide Updated - November 2018 Software Version - 6.2.0 Contents
Quest® Stat® 6.2.0 System Administration Guide © 2018 Quest Software Inc. ALL RIGHTS RESERVED. This guide contains proprietary information protected by copyright. The software described in this guide is furnished under a software license or nondisclosure agreement. This software may be used or copied only in accordance with the terms of the applicable agreement. No part of this guide may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying and recording for any purpose other than the purchaser’s personal use without the written permission of Quest Software Inc. The information in this document is provided in connection with Quest Software products. No license, express or implied, by estoppel or otherwise, to any intellectual property right is granted by this document or in connection with the sale of Quest Software products. EXCEPT AS SET FORTH IN THE TERMS AND CONDITIONS AS SPECIFIED IN THE LICENSE AGREEMENT FOR THIS PRODUCT, QUEST SOFTWARE ASSUMES NO LIABILITY WHATSOEVER AND DISCLAIMS ANY EXPRESS, IMPLIED OR STATUTORY WARRANTY RELATING TO ITS PRODUCTS INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTY OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, OR NON-INFRINGEMENT. IN NO EVENT SHALL QUEST SOFTWARE BE LIABLE FOR ANY DIRECT, INDIRECT, CONSEQUENTIAL, PUNITIVE, SPECIAL OR INCIDENTAL DAMAGES (INCLUDING, WITHOUT LIMITATION, DAMAGES FOR LOSS OF PROFITS, BUSINESS INTERRUPTION OR LOSS OF INFORMATION) ARISING OUT OF THE USE OR INABILITY TO USE THIS DOCUMENT, EVEN IF QUEST SOFTWARE HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. Quest Software makes no representations or warranties with respect to the accuracy or completeness of the contents of this document and reserves the right to make changes to specifications and product descriptions at any time without notice.