Tuning Java ServersInfoQ Software Architects' Newsletter A monthly overview of things you need to know as an architect or aspiring architect. View an example
» principles of high performance programs
principles of high performance programs Monday, December 10th, 2012 by arvid This article is an attempt to sum up a small number of generic rules that appear to be useful rules of thumb when creating high performing programs. It is structured by first establishing some fundamental causes of performance hits followed by their extensions. memory latency A significant source of performance degradatio
LAN Ethernet Maximum Rates, Generation, Capturing & Monitoring - NST Wiki
LAN Ethernet Maximum Rates, Generation, Capturing & Monitoring Introduction Designing and managing an IP network requires an in-depth understanding of both the network infrastructure and the performance of devices that are attached, including how packets are handled by each network device. Network computing engineers typically refer to the performance of network devices by using the speed of the i
サーバ負荷分散概論 - KLablabWiki
特集のはじめに 本特集のメインテーマは『サーバ負荷分散』です。 負荷分散というと むずかしそう 機器が高価 大規模向け というイメージが先行して、敬遠している人は多いのではないかと思います。 実は、今回の特集はそんなあなたのために書きました。 本特集を読み終えたあと、きっとその印象は おもしろそう 安い 手軽に使える に変わっているでしょう。 ではではさっそく本題に入りましょう。まず本章では「サーバ負荷分散」一般についてざっと説明し、次章以降でより具体的な実現方法を解説していきたいと思います。 なぜサーバ負荷分散をするのか？ 『サーバ負荷分散』[1]をひとことでいうと、「1つのサービスを複数のサーバで行うこと」です。では、どうして複数のサーバでサービスしたいのでしょうか？ どんな利点があるのでしょうか？ 大別するとそれは2つあります。[2] 性能 まず1つめの利点は性能向上です。 例
How to improve JPA performance by 1,825%
The Java Persistence API (JPA) provides a rich persistence architecture. JPA hides much of the low level dull-drum of database access, freeing the application developer from worrying about the database, and allowing them to concentrate on developing the application. However, this abstraction can lead to poor performance, if the application programmer does not consider how their implementation affe
Off-CPU Analysis
Performance issues can be categorized into one of two types: On-CPU: where threads are spending time running on-CPU. Off-CPU: where time is spent waiting while blocked on I/O, locks, timers, paging/swapping, etc. Off-CPU analysis is a performance methodology where off-CPU time is measured and studied, along with context such as stack traces. It differs from CPU profiling, which only examines threa
PerformanceTuning < MAX < TWiki
Network Performance Testing This page is intended to bring together a number of approaches and resources relating to testing and tuning end systems to improve network performance and the throughput experienced by users applications and the movement of large data files. The focus is on understanding how to tune and debug end systems to obtain the highest throughput performance possible with the sy
Tuning Systems for TCP/IP Performance on High Latency Networks
1 Tuning Systems for TCP/IP Performance on High Latency Networks Worldwide LHC Computing Grid Tier-2 Workshop in Asia Mark Bowden, Wenji Wu, Matt Crawford (bowden@fnal.gov, wenji@fnal.gov, crawdad@fnal.gov) 01 Dec 2006 2 TCP_buffer_size = RTT * BW 160 KBytes = 125 msec * 10 Mbps 1.6 MBytes = 125 msec * 100 Mbps 16 MBytes = 125 msec * 1000 Mbps 160 MBytes = 125 msec * 10000 Mbps example: Chicago-CE
Software Optimization: A Systematic Approach
Looking for Python Tutoring? Remote and local (NYC) slots still available! Email me at jeff@jeffknupp.com for more info. Introduction What follows is the first in a series of articles on developing a formal methodology for software optimization I've been working on for some time. Each week, I'll post the newest installment here (they're all written, I'm just wary of dumping the whole thing here al
Performance Tweaks and Tools For Linux | PDF | Transmission Control Protocol | Device Driver
The document provides tools and techniques for profiling and debugging Linux systems and Ruby applications. It discusses the lsof tool for listing open files, strace for tracing system calls, tcpdump for dumping network traffic, Google's perftools for profiling CPU usage, and a perftools.rb gem for profiling Ruby code. Examples are given for using these tools to analyze memory usage, thread schedu
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What Linux Can Learn from Solaris Performance, and Vice-Versa | Triton DataCenter