Prakash Raghavendra

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In this paper we describe how to support atomics across multiple devices in heterogeneous processors. Specifically, this paper provides an overview of how OpenCL 2.0 and Heterogeneous System Architecture (HSA) atomics are supported on integrated CPU-GPU processors called Accelerated Processing Units (APUs). Recently, the C11 and C++11 standards have(More)
The vision of super computer at every desk can be realized by powerful and highly parallel CPUs or GPUs or APUs. Graphics processors once specialized for the graphics applications only, are now used for the highly computational intensive general purpose applications. Very expensive GFLOPs and TFLOP performance has become very cheap with the GPGPUs. Current(More)
Cloud Computing is the evolution of a variety of technologies that have come together to alter an organization's approach to building IT infrastructure. It borrows from several computing techniques — grid computing, cluster computing, software-as-a-service, utility computing, autonomic computing and many more. It provides a whole new deployment model(More)
Today, the challenge is to exploit the parallelism available in the way of multi-core architectures by the software. This could be done by re-writing the application, by exploiting the hardware capabilities or expect the compiler/software runtime tools to do the job for us. With the advent of multi-core architectures ([1] [2]), this problem is becoming more(More)
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