Tuning Your Apps For Optimal Performance
Building a plan to constantly improve the speed of your code
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Hot-Rodding Windows and Linux App Performance with CUDA-Based Plugins
Adding GPU capabilities to existing Windows and Linux apps can be done simply using plugins and the built-in support found in CUDA. This easy form of dynamic loading enables CUDA to be used selectively to hugely accelerate individual tasks within a larger application.
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Python 3.2 Beta 1 Introduces New Concurrency Features
Python 3.2 Beta 1 adds a futures library for concurrent programming that is part of a new concurrent top-level package. The main goal is to simplify the parallelization of code and to make it simple to launch and control asynchronous and concurrent operations.
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This Week's Multicore Reading List
A list of book releases compiled by Dr. Dobb's to keep you up-to-date on parallel programming and multicore technology.
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ParBenCCh 1.0 Parallel C++ Benchmarking Suite
A C and C++ application suite designed to characterize compiler optimization capabilities and more
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Intel Threading Building Blocks (TBB) 3.0
We are happy to introduce Intel Threading Building Blocks 3.0 (TBB). TBB 3.0 builds on the past four years of TBB by adding to the breadth and depth of features in the library, improving performance, and in the Windows version utilizing the latest developments from Microsoft to support parallelism.
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Engineering Parallel Applications with Tunable Architectures
Introducing a new architecture description language based on parallel patterns
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This Week's Multicore Reading List
"C# Design and Development: Expert One on One"; "Linux Programmer's Toolbox"
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A Library-Based Approach to Threading for Performance
Libraries play an important role in threading software to run faster on multicore platforms
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Parallel Pattern 6: Partition
A straightforward way to express both data locality and isolation
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Fun with Locks and Waits: Performance Tuning
Figuring out where to make changes to get the biggest performance improvement
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Optimization Techniques for Intel Multicore Processors
The key is understanding the inherent parallelism in applications
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XcalableMP: A Performance-Aware Scalable Parallel Programming Language for Distributed Memory System
Lets users develop parallel programs for distributed memory systems easily
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Cray Acquires PathScale Compiler Suite
Company to contribute parts of PathScale IP to open source community
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How To Sound Like a Parallel Programming Expert: Part 4
Writing parallel software
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End-to-End Development with Intel Parallel Studio
A four-stage development cycle
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Intel Releases Parallel Studio 1.0
Includes technology preview of Parallel Advisor
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Managing Multi-Core Projects, Part 4: The Enterprise Development Cycle Meets Multi-Core
How does multi-core change the development cycle for enterprise software?
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Transitioning Software to Future Generations of Multi-Core
The industry shift to increasing levels of hardware parallelism through higher numbers of execution cores in mainstream processors requires change on the part of software makers. One key requirement is to look ahead to the hardware resources that are likely to be available in the future and to make appropriate architectural decisions in advance to accommodate them. This paper contributes to the discussion about planning for those developments.
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Managing Multi-Core Projects, Part 2: HPC Project Implementation
Directing a parallel-programming development project requires knowing the components, knowing the tools to use, and knowing your customers. Part 2 of our management series spotlights some of the lessons learned in fielding parallel HPC applications.
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AJAX Makes Your Applications Sizzle on WebSphere Application Server Community Edition
Learn how to create a CRM application based on AJAX and use this code to kick-start your development of other rich, scalable Web applications on IBM WebSphere Application Server Community Edition
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