Performance

Episode 14. Optimizing for Performance – The tools

In the second part of optimization, we talk about the tools (or more properly algorithms) that you can use to optimize a piece of code. Ever wonder how to make a piece of code faster? or difference between caching and Divide-and-Conquer? then tune in! You’ll become the McGyver of code optimization.

Fork/Join Java 7 (http://docs.oracle.com/javase/tutorial/essential/concurrency/forkjoin.html)
Guava (http://code.google.com/p/guava-libraries/)
Charlie Hunt’s book (http://www.amazon.com/Java-Performance-Charlie-Hunt/dp/0137142528)
OpenCL for Java (http://www.jocl.org/)
Aparapi (http://developer.amd.com/zones/java/aparapi/Pages/default.aspx)

Questions, feedback or comments!comments@javapubhouse.com

Subscribe to our podcast! (http://javapubhouse.libsyn.com/rss)
ITunes link (http://itunes.apple.com/us/podcast/java-pub-house/id467641329)
Java 7 Recipes book! (http://www.amazon.com/Java-7-Recipes-Problem-Solution-Approach/dp/1430240563)

Episode 13. Optimizing for Performance

We all love speed, code speed that is! In this podcast we delve into code optimizations, and what does it mean to optimize for speed. We go over what is the mind-state that you need as you optimize code and offer sneaky shortcuts that allows 10-fold improvement with very little code change (Caching, or pregenerating, or timed-updates). More importantly we go over the process on defining when you have “arrived” at a good optimization point, and hopefully help you optimize what is really important (measuring for performance). If you need to scale up/out and around, listen to this episode!

If you feel you would like to share your optimization experience, go to https://groups.google.com/group/javapubhouse, and post!

Questions, feedback or comments!comments@javapubhouse.com

Subscribe to our podcast! (http://javapubhouse.libsyn.com/rss)
ITunes link (http://itunes.apple.com/us/podcast/java-pub-house/id467641329)
Java 7 Recipes book! (http://www.amazon.com/Java-7-Recipes-Problem-Solution-Approach/dp/1430240563)

Episode 7. Threads, Priorities, and Swing’s Golden Rule

In this episode we talk about Threads and Threading, the difference between Daemon and User Threads, and why changing priorities is not for the weak of heart. Also we cover Swing’s golden Threading rule (with the Event Dispatching Thread). If you ever typed new Thread(), or if you heard to be careful about Swing and Threading, this episode is for you!

 

Episode 5. Producing and Consuming, ThreadPoolExecutor, and Latency vs Throughput

In this podcast we dive into the age-old producer and consumer problem, talked about the different aspects of it (what does it really solve?), and explain the difference between throughput vs latency. Lastly we discuss the ThreadPoolExecutor and how to fine tune it for your particular project needs!

 

Episode 3. Memory leaks, memory references and garbage collections!

This episode goes deep into memory in Java, understanding how memory leaks happen (and how to solve them!), also how to design to avoid memory leaks, weak and soft references, and how the Garbage collector works (Eden, Tenured, Perm). This podcast will help everyone that needs to take care of a memory leak!

Kudos to VisualVM and VisualGC!

 

Episode 2. Deadlock, Livelock, Escaped locks, and wait/notify oh my!

In this episode of Java pub house, we talk about Deadlocks, livelocks (and other spooky things). Most importantly we talk on how to spot them (using jstack, or visualvm), and how to program defensively against them. We also talk about escaped locks (the source of most deadlocks), and the wait/notify language construct. Finally we describe the unfairness of the lock (locks are not “fair” by default), and why is it so.

Happy Programming!

Episode 1. Volatile, and Synchronized

On this Episode, we talk about the keyword “volatile”, and what does it really mean. Even if you are a multithreading guru, this chapter goes in deep of the different things that volatile protects you from, including L2 caches and code re-ordering. We also cover the use of synchronized, and why, even though is convenient, it might create more headache than it actually solves.

Happy Programming!