The document discusses ways to make Ruby CGI scripts faster. It explains that process invocation and library loading are the main reasons CGI scripts are slow. Various case studies are presented on optimizing code by lazy-loading libraries, avoiding unnecessary objects, and parsing query strings efficiently. Benchmark results show performance improvements from these techniques.
Shared Memory Performance: Beyond TCP/IP with Ben Cotton, JPMorganHazelcast
In this webinar you’ll learn the importance of Advanced Data Locality and Data IPC Transports with respect to Java distributed cache data grids. This is information that is super-crucial to the HPC Linux supercomputing community. The presenter will show how by using native /dev/shm as an IPC transport we can achieve latencies 1,000x faster than TCP/IP.
We’ll cover the following topics:
-Why going off-heap is fundamental to meeting real-time SLAs
-Why traditional grid transports (TCP/IP) are not good enough for the HPC Linux supercomputing community
-Why we need something more than TCP/IP
-Live Q&A Session
Presenter:
Ben Cotton, Consultant at JPMorgan
Ben is has been an IT Consultant to Financial Services Industry for nearly 20 years. His specializations lie in open source, transactions, caching, datagrids, fixed income & derivatives trading systems.
Ben is active in the following communities:
Java Community Process Member
JSR-156 expert group: Java XML Transactions API
JSR-107 expert group: Java Caching API
JSR-347 expert group: Java Data Grids API
RedHat Community Member (Fedora, Infinispan, JBoss XTS) Code Contributor
At LinkedIn we run lots of Java services on Linux boxes. Java and Linux are a perfect pair. Except when they're not; then there's fireworks. This talk describes 5 situations we encountered where Java interacted with normal Linux behavior to create stunningly sub-optimal application behavior like minutes-long GC pauses. We'll deep dive to show What Java Got Wrong, why Linux behaves the way it does, and how the two can conspire to ruin your day. Finally we'll examine actual code samples showing how we fixed or hid the problems.
Some of the biggest issues at the center of analyzing large amounts of data are query flexibility, latency, and fault tolerance. Modern technologies that build upon the success of “big data” platforms, such as Apache Hadoop, have made it possible to spread the load of data analysis to commodity machines, but these analyses can still take hours to run and do not respond well to rapidly-changing data sets.
A new generation of data processing platforms -- which we call “stream architectures” -- have converted data sources into streams of data that can be processed and analyzed in real-time. This has led to the development of various distributed real-time computation frameworks (e.g. Apache Storm) and multi-consumer data integration technologies (e.g. Apache Kafka). Together, they offer a way to do predictable computation on real-time data streams.
In this talk, we will give an overview of these technologies and how they fit into the Python ecosystem. As part of this presentation, we also released streamparse, a new Python that makes it easy to debug and run large Storm clusters.
Links:
* http://parse.ly/code
* https://github.com/Parsely/streamparse
* https://github.com/getsamsa/samsa
Shared Memory Performance: Beyond TCP/IP with Ben Cotton, JPMorganHazelcast
In this webinar you’ll learn the importance of Advanced Data Locality and Data IPC Transports with respect to Java distributed cache data grids. This is information that is super-crucial to the HPC Linux supercomputing community. The presenter will show how by using native /dev/shm as an IPC transport we can achieve latencies 1,000x faster than TCP/IP.
We’ll cover the following topics:
-Why going off-heap is fundamental to meeting real-time SLAs
-Why traditional grid transports (TCP/IP) are not good enough for the HPC Linux supercomputing community
-Why we need something more than TCP/IP
-Live Q&A Session
Presenter:
Ben Cotton, Consultant at JPMorgan
Ben is has been an IT Consultant to Financial Services Industry for nearly 20 years. His specializations lie in open source, transactions, caching, datagrids, fixed income & derivatives trading systems.
Ben is active in the following communities:
Java Community Process Member
JSR-156 expert group: Java XML Transactions API
JSR-107 expert group: Java Caching API
JSR-347 expert group: Java Data Grids API
RedHat Community Member (Fedora, Infinispan, JBoss XTS) Code Contributor
At LinkedIn we run lots of Java services on Linux boxes. Java and Linux are a perfect pair. Except when they're not; then there's fireworks. This talk describes 5 situations we encountered where Java interacted with normal Linux behavior to create stunningly sub-optimal application behavior like minutes-long GC pauses. We'll deep dive to show What Java Got Wrong, why Linux behaves the way it does, and how the two can conspire to ruin your day. Finally we'll examine actual code samples showing how we fixed or hid the problems.
Some of the biggest issues at the center of analyzing large amounts of data are query flexibility, latency, and fault tolerance. Modern technologies that build upon the success of “big data” platforms, such as Apache Hadoop, have made it possible to spread the load of data analysis to commodity machines, but these analyses can still take hours to run and do not respond well to rapidly-changing data sets.
A new generation of data processing platforms -- which we call “stream architectures” -- have converted data sources into streams of data that can be processed and analyzed in real-time. This has led to the development of various distributed real-time computation frameworks (e.g. Apache Storm) and multi-consumer data integration technologies (e.g. Apache Kafka). Together, they offer a way to do predictable computation on real-time data streams.
In this talk, we will give an overview of these technologies and how they fit into the Python ecosystem. As part of this presentation, we also released streamparse, a new Python that makes it easy to debug and run large Storm clusters.
Links:
* http://parse.ly/code
* https://github.com/Parsely/streamparse
* https://github.com/getsamsa/samsa
Are you a Java developer wondering what it means to have your application running in the cloud. This session will provide a peek into how the JVM is adapting to running in the cloud and what Java developers need to be aware to ensure they get the most of running in the cloud.
The session will pick an example spring application and tune it stage by stage at the end of which we have an application that is fully optimized and takes advantage of every aspect of the running in a cloud
How to Leverage Go for Your Networking NeedsDigitalOcean
Watch this Tech Talk: https://do.co/video_singuva
Highlights from Sneha Inguva’s networking journey through Go. Sneha discusses the useful packages, key learnings, and struggles faced while building a variety of networking services within and outside of DigitalOcean. Walk away with a clear understanding of how to specifically leverage Go for your own networking needs.
About the Presenter
Sneha Inguva is a Software Engineer on the Networking team at DigitalOcean. She enjoys building cloud products by day and debugging ominous context-canceled errors by night. In her spare time, she professionally lounges around with her cat.
New to DigitalOcean? Get US $100 in credit when you sign up: https://do.co/deploytoday
To learn more about DigitalOcean: https://www.digitalocean.com/
Follow us on Twitter: https://twitter.com/digitalocean
Like us on Facebook: https://www.facebook.com/DigitalOcean
Follow us on Instagram: https://www.instagram.com/thedigitalocean/
We're hiring: http://do.co/careers
Slides from #PromCon2018 Munich.
https://promcon.io/2018-munich/talks/thanos-prometheus-at-scale/
Bartłomiej Płotka
Fabian Reinartz
The Prometheus Monitoring system has been thriving for several years. Along with its powerful data model, operational simplicity and reliability have been a key factor in its success. However, some questions were still largely unaddressed to this day. How can we store historical data at the order of petabytes in a reliable and cost-efficient way? Can we do so without sacrificing responsive query times? And what about a global view of all our metrics and transparent handling of HA setups?
Thanos takes Prometheus' strong foundations and extends it into a clustered, yet coordination free, globally scalable metric system. It retains Prometheus's simple operational model and even simplifies deployments further. Under the hood, Thanos uses highly cost-efficient object storage that's available in virtually all environments today. By building directly on top of the storage format introduced with Prometheus 2.0, Thanos achieves near real-time responsiveness even for cold queries against historical data. All while having virtually no cost overhead beyond that of the underlying object storage.
We will show the theoretical concepts behind Thanos and demonstrate how it seamlessly integrates into existing Prometheus setups.
A brief explanation on how the JVM loads and execute its code is done here. Register and stack based execution are explained, and different garbage collection algorithms are shown using graphs to make it easy to understand what happens under the hood. This talk uses the Java Virtual Machine as a main example, but most of the concepts extends to any modern virtual machine available today.
Developing High Performance Application with Aerospike & GoChris Stivers
In this presentation, Chris Stivers, introduces the audience to Aerospike and provides tips on improving performance of Application written in Go. Tips include how to use memory more effectively in Go, and using Aerospike for high throughput / low latency transactions.
Практический опыт профайлинга и оптимизации производительности Ruby-приложенийOlga Lavrentieva
Алексей Туля, Senior Software Developer в Sam Solutions
«Практический опыт профайлинга и оптимизации производительности Ruby-приложений»
В своем докладе Алексей сделает краткий обзор различных реализаций Ruby, попытается найти причины, почему Ruby медленный. Рассмотрит вопрос сборки мусора в Ruby и вызова методов – почему в Ruby это дорого. Расскажет и покажет, что делать, чтобы поднять производительность, проведет обзор утилит для поиска проблемных мест, обзор профайлеров и расскажет, как интерпретировать результаты.
Доклад в основном нацелен на практический подход по поиску проблем. Материал предназначен для пользователей Linux, поэтому все практические советы будут для ОС Linux.
Are you a Java developer wondering what it means to have your application running in the cloud. This session will provide a peek into how the JVM is adapting to running in the cloud and what Java developers need to be aware to ensure they get the most of running in the cloud.
The session will pick an example spring application and tune it stage by stage at the end of which we have an application that is fully optimized and takes advantage of every aspect of the running in a cloud
How to Leverage Go for Your Networking NeedsDigitalOcean
Watch this Tech Talk: https://do.co/video_singuva
Highlights from Sneha Inguva’s networking journey through Go. Sneha discusses the useful packages, key learnings, and struggles faced while building a variety of networking services within and outside of DigitalOcean. Walk away with a clear understanding of how to specifically leverage Go for your own networking needs.
About the Presenter
Sneha Inguva is a Software Engineer on the Networking team at DigitalOcean. She enjoys building cloud products by day and debugging ominous context-canceled errors by night. In her spare time, she professionally lounges around with her cat.
New to DigitalOcean? Get US $100 in credit when you sign up: https://do.co/deploytoday
To learn more about DigitalOcean: https://www.digitalocean.com/
Follow us on Twitter: https://twitter.com/digitalocean
Like us on Facebook: https://www.facebook.com/DigitalOcean
Follow us on Instagram: https://www.instagram.com/thedigitalocean/
We're hiring: http://do.co/careers
Slides from #PromCon2018 Munich.
https://promcon.io/2018-munich/talks/thanos-prometheus-at-scale/
Bartłomiej Płotka
Fabian Reinartz
The Prometheus Monitoring system has been thriving for several years. Along with its powerful data model, operational simplicity and reliability have been a key factor in its success. However, some questions were still largely unaddressed to this day. How can we store historical data at the order of petabytes in a reliable and cost-efficient way? Can we do so without sacrificing responsive query times? And what about a global view of all our metrics and transparent handling of HA setups?
Thanos takes Prometheus' strong foundations and extends it into a clustered, yet coordination free, globally scalable metric system. It retains Prometheus's simple operational model and even simplifies deployments further. Under the hood, Thanos uses highly cost-efficient object storage that's available in virtually all environments today. By building directly on top of the storage format introduced with Prometheus 2.0, Thanos achieves near real-time responsiveness even for cold queries against historical data. All while having virtually no cost overhead beyond that of the underlying object storage.
We will show the theoretical concepts behind Thanos and demonstrate how it seamlessly integrates into existing Prometheus setups.
A brief explanation on how the JVM loads and execute its code is done here. Register and stack based execution are explained, and different garbage collection algorithms are shown using graphs to make it easy to understand what happens under the hood. This talk uses the Java Virtual Machine as a main example, but most of the concepts extends to any modern virtual machine available today.
Developing High Performance Application with Aerospike & GoChris Stivers
In this presentation, Chris Stivers, introduces the audience to Aerospike and provides tips on improving performance of Application written in Go. Tips include how to use memory more effectively in Go, and using Aerospike for high throughput / low latency transactions.
Практический опыт профайлинга и оптимизации производительности Ruby-приложенийOlga Lavrentieva
Алексей Туля, Senior Software Developer в Sam Solutions
«Практический опыт профайлинга и оптимизации производительности Ruby-приложений»
В своем докладе Алексей сделает краткий обзор различных реализаций Ruby, попытается найти причины, почему Ruby медленный. Рассмотрит вопрос сборки мусора в Ruby и вызова методов – почему в Ruby это дорого. Расскажет и покажет, что делать, чтобы поднять производительность, проведет обзор утилит для поиска проблемных мест, обзор профайлеров и расскажет, как интерпретировать результаты.
Доклад в основном нацелен на практический подход по поиску проблем. Материал предназначен для пользователей Linux, поэтому все практические советы будут для ОС Linux.
JCON Online 2021, International Java Community Conference, 07.10.21, Moritz Kammerer (@Moritz Kammerer, Expert Software Engineer at QAware).
== Please download slides in case they are blurred! ===
In his talk we have had a look at how Microservices can be developed with Micronaut. In our slides you can find out if it kept its promise.
Three tricks how to understand what's happening inside of .NET Core app running on Linux: perf, lttng and lldb. As unrelated bonus, last slides have a brief intro into Google Cloud Platform
Transactional writes to cloud storage with Eric LiangDatabricks
We will discuss the three dimensions to evaluate HDFS to S3: cost, SLAs (availability and durability), and performance. He then provided a deep dive on the challenges in writing to Cloud storage with Apache Spark and shared transactional commit benchmarks on Databricks I/O (DBIO) compared to Hadoop.
Java Day 2021, WeAreDevelopers, 2021-09-01, online: Moritz Kammerer (@Moritz Kammerer, Expert Software Engineer at QAware).
== Please download slides in case they are blurred! ===
In this talk, we took a look at how Microservices can be developed with Micronaut. Have a look if it has kept its promises.
Drizzle—Low Latency Execution for Apache Spark: Spark Summit East talk by Shi...Spark Summit
Drizzle is a low latency execution engine for Apache Spark
that is targeted at stream processing and iterative workloads.
Currently, Spark uses a BSP computation model, and notifies the
scheduler at the end of each task. Invoking the scheduler at the end of each task adds overheads and results in decreased throughput and increased latency. In Drizzle, we introduce group scheduling, where multiple batches (or a group) of computation are scheduled at once.
This helps decouple the granularity of task execution from scheduling and amortize the costs of task serialization and launch. Our experiments on a 128 node EC2 cluster show that Drizzle can achieve end-to-end streaming latencies of less than 100ms and can get up to 3.5x lower latency than Spark Streaming. Compared to Apache Flink, a record-at-a-time streaming system, we show that Drizzle can recover around 4x faster from failures and that Drizzle has up to 13x lower latency during recovery.
Container Performance Analysis Brendan Gregg, NetflixDocker, Inc.
Containers pose interesting challenges for performance monitoring and analysis, requiring new analysis methodologies and tooling. Resource-oriented analysis, as is common with systems performance tools and GUIs, must now account for both hardware limits and soft limits, as implemented using resource controls including cgroups. The interaction between containers can also be examined, and noisy neighbors either identified of exonerated. Performance tooling can also need special usage or workarounds to function properly from within a container or on the host, to deal with different privilege levels and name spaces. At Netflix, we're using containers for some microservices, and care very much about analyzing and tuning our containers to be as fast and efficient as possible. This talk will show how to successfully analyze performance in a Docker container environment, and navigate differences encountered.
go-git is a 100% Go libray used to interact with git repositories. Even if it already supports most of the functionality it still lags a bit in performance when compared with the git CLI or some other libraries. I'll explain some of the problems that we face when dealing with git repos and some examples of performance improvements done to the library.
Slides de la présentation faite lors du PerfUG #3 du 29 août 2013 chez Octo Technology.
Sujet : comment déterminer rapidement les performances unitaires dont un système informatique est capable.
Create C++ Applications with the Persistent Memory Development KitIntel® Software
Persistent memory retains data after a program crash or power failure. This demonstration shows how to make your application aware of persistent memory using the Persistent Memory Development Kit and includes a C++ code sample walk-through.
Router is one of the most important feature or component in Web application framework,
ant it is also one of the performance bottlenecks of framework.
In this session, I'll show you how to make router much faster than ever.
Oktest - a new style testing library for Python -kwatch
Oktest is a new-style testing library for Python. It helps you to read & write tests very much. Oktest is available with (or without) standard 'unittest' module.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
How to Make Ruby CGI Script Faster - CGIを高速化する小手先テクニック -
1. Nagoya RubyKaigi 02
How to Make
Ruby CGI Script Faster
CGI
makoto kuwata
http://www.kuwata-lab.com/
2. What I'll talk and not
I talk about I don't talk about
Why CGI is so slow? Scale out
How to improve your Database
code?
Key Value Store
Or other kool topics
5. Benchmark
Process Invocation require 'cgi'
cgi = CGI.new render HTML
1.80%
0.87%
39.55%
57.78%
Mac OS X 10.6
Ruby 1.8.7-p334
Core2 Duo 2GHz
https://gist.github.com/850390
6. Why CGI is so slow?
FACT
Process invocation is slow
TRUTH
Library loading is much slow
7. Benchmark of 'require'
(none) 6.15 1.8.7-p334
erb 9.26
time 15.9 Library loading
uri 16.15 is much slower
fileutils 17.26 than process
cgi 17.31 invocation
tmpdir 17.84
(
pstore 19.19
date2 19.4 )
openssl 21.92
tempfile 22.53
cgi/session 30.18
yaml 32.27
rexml/document 40.96
0 10 20 30 40 50 (ms)
https://gist.github.com/850386