AMD announced availability of the AMD APP SDK 2.8 and the AMD CodeXL unified tool suite to provide developers the tools and resources needed to accelerate applications with AMD accelerated processing units (APUs) and graphics processing units (GPUs). The APP SDK 2.8 and CodeXL tool suite provides access to code samples, white papers, libraries, and tools to leverage the processing power of heterogeneous compute with OpenCL™, C++, DirectCompute and more.
In short, now you can do more with programming on platforms which are powered by AMD microprocessor.
Parallel programming, a technique for programming optimisation and acceleration, was made popular to the general programming community by NVIDIA through its GPU platform. Refer to Malaysia Technology News for some details.
The idea of parallel programming is that besides relying purely on optimising the source code to yield better performance, in which the source code will be recompiled into a more efficient binaries by the compilers - a software can be accelerated further by implementing parallelism. To do this, the source code can be designed to utilise the parallel computing resources of such platforms directly through API calls.
The way I see it, amidst falling sales, AMD is now investing on the trend of parallel programming to reach new market segments.
AMD offers a better spectrum of choices for developers compared to NVIDIA. Its microprocessor's parallel programming capabilities not only include GPU (Graphical Processing Unit), but APU (Accelerated Processing Unit) as well.
More information.
In short, now you can do more with programming on platforms which are powered by AMD microprocessor.
Parallel programming, a technique for programming optimisation and acceleration, was made popular to the general programming community by NVIDIA through its GPU platform. Refer to Malaysia Technology News for some details.
The idea of parallel programming is that besides relying purely on optimising the source code to yield better performance, in which the source code will be recompiled into a more efficient binaries by the compilers - a software can be accelerated further by implementing parallelism. To do this, the source code can be designed to utilise the parallel computing resources of such platforms directly through API calls.
The way I see it, amidst falling sales, AMD is now investing on the trend of parallel programming to reach new market segments.
AMD offers a better spectrum of choices for developers compared to NVIDIA. Its microprocessor's parallel programming capabilities not only include GPU (Graphical Processing Unit), but APU (Accelerated Processing Unit) as well.
More information.
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