Fri Apr 12 00:44:19 HKT 2019
Nothing specific, mostly code clean up, refactoring and simplification, the performance boost was a surprise. <- This is a good one - http://bad-concurrency.blogspot.com.au[..]12/07/disruptor-v3-faster-hopefully.html
Is there anything we can do about this when designing algorithms and data-structures? Yes there is a lot we can do. If we perform chunks of work on data that is co-located, and we stride around memory in a predictable fashion, then our algorithms can be many times faster. For example rather than using bucket and chain hash tables, like in the JDK, we can employ hash tables using open-addressing with linear-probing. Rather than using linked-lists or trees with single items in each node, we can store an array of many items in each node. - http://mechanical-sympathy.blogspot.com.au[..]emory-access-patterns-are-important.html
Skip lists are used instead of b-trees because b-trees don’t scale. - http://highscalability.com[..]ast-mvcc-inmem-lockfree-codegen-and.html
Beware about the performance issue of static initalization - http://stackoverflow.com[..]-cause-problems-with-multi-threading-how
Experiment show why arraylist is better in most cases - http://www.javaadvent.com/2013/12/arraylist-vs-linkedlist.html
How to design low latency application in java - http://vanillajava.blogspot.com.au[..]5/chronicle-and-low-latency-in-java.html
Suggestion about how to determine number of thread pool - http://venkateshcm.com[..]rmine-Web-Applications-Thread-Poll-Size/
Beware the performance penalty of logging - https://plumbr.eu/blog/locking-and-logging
Keep thing dynamic - http://highscalability.com[..]ciples-of-high-performance-programs.html
Discuss about developing low latency financial application - http://queue.acm.org/detail.cfm?ref=rss&id=2770868
Discussion of object pooling - http://highscalability.com[..]-but-forgotten-trick-object-pooling.html http://coffeenco.de[..]m_performance_part_1_object_pooling.html
Efficiency - the amount of work you need to do.
Performance - how fast you can do that work
Efficiency - governed by your algorithm
Performance - governed by your data structures.
Turning off power save mode on the CPU reduced brought the max latency from 11 msec down to 8 msec.
Guaranteeing threads will always have CPU resources using CPU isolation and thread affinity brought the maximum latency down to 14 microseconds.
About design for performance for webapi - http://tech.forter.com[..]y-decision-as-a-service-design-patterns/
check list - http://techbeacon.com[..]ery-software-development-team-should-ask
Beware if system utilization over 80% - http://www.infoq.com/cn/news/2016/02/utilisation-wait-latency http://robharrop.github.io[..]/20/service-latency-and-utilisation.html
scalable-io-events-vs-multithreading-based - https://thetechsolo.wordpress.com[..]lable-io-events-vs-multithreading-based/
How to find out bottleneck - https://vanilla-java.github.io[..]entile-latencies-in-Chronicle-Queue.html
Compiler Performance and LLVM - http://pling.jondgoodwin.com/post/compiler-performance/
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