Many Android* devices have processors with more than one core and knowing how to develop multithreaded applications has become important in the mobile industry. Intel has developed a valuable tool for developing parallel applications called Intel® Threading Building Blocks (Intel® TBB). The Intel® TBB is a cross-platform library of templates for creating parallel programs. It creates and synchronizes streams of data, hiding the details of the architecture and allowing you to work at a higher level of abstraction. Intel® TBB works on all architectures.
Recently, the new Android L 64-bit OS became available. In this paper I will show you how easy it is to develop parallel applications for Android L 64 bit with Intel® Threading Building Blocks (Intel® TBB). The Intel TBB is a cross-platform library of templates for creating parallel programs. It creates and synchronizes streams of data, hiding the details of the architecture and allowing you to work at a higher level of abstraction. Intel TBB works on all architectures. For Android, use version 4.3 and above.
This article describes a parallel merge sort code, and why it is more scalable than parallel quicksort or parallel samplesort. The code relies on the C++11 “move” semantics. It also points out a scalability trap to watch out for with C++. The attached code has implementations in Intel® Threading Building Blocks (Intel® TBB), Intel® Cilk™ Plus, and OpenMP*.
So I morphed my title from a Marine Corps. slogan - I know my late father and my not-so-late brother (both former USMC Seargents) would approve.
In the graduate course Concurrent Object Oriented Languages, taught at York University, Toronto, students do three assignment and write a paper based on these assignments.
The objective of the first assignment is to find a nontrivial concurrent algorithm in the literature. In the second assignment, the aim is the implementation of the concurrent algorithm presented in the first assignment in Java. The focus of the third assignment is to apply tools to verify the concurrent Java program of the second assignment.
This course covers the following topics:
Explicit Threading in Java.
- Lab: Explicit Threading in Java.
- JSR-166y: Higher Abstraction. Functional Programming.
- Labs: JSR-166y
- Hadoop: Mainly model parallelization. Very large scale.
- Lab: Hadoop
- Google App Engine: Simple and Scalable MVC for simple needs.
- Lab: Google App Engine.
The paper summarizes an assignment on the European Football Elimination Problem which was given to my students in this year\'s lecture on parallel and distributed algorithms. The students were asked to use Intel\'s TBB 3.0 to solve the assignment. The material also contains an application named Team Planer which can be used to generate input files for testing purposes.
The lecture given here is the first part in the “Introduction to Parallel Programming” video series. This part endeavors to define parallel computing, explain why parallel computing is becoming mainstream, and explain why explicit parallel programming is necessary. This part sets the tone for the other 11 parts in the series.
Running time: 9:51
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