Each new generation of GPUs vastly increases the resources available to GPGPU
programs. GPU programming models (like CUDA) were designed to scale to use these …

Ocelot is a dynamic compilation framework designed to map the explicitly data parallel
execution model used by NVIDIA CUDA applications onto diverse multithreaded platforms …

Heterogeneous parallel computing platforms, which are composed of different processors
(eg, CPUs, GPUs, FPGAs, and DSPs), are widening their user base in all computing …

The growing interest in GPU programming has brought renewed attention to the Single
Instruction Multiple Data (SIMD) execution model. SIMD machines give application …

We address the problem of applying powerful pattern recognition algorithms based on
kernels to efficient visual tracking. Recently S. Avidan,(2001) has shown that object …

Modern throughput processors such as GPUs achieve high performance and efficiency by
exploiting data parallelism in application kernels expressed as threaded code. One draw …

While parallelism remains the main source of performance, architectural implementations
and programming models change with each new hardware generation, often leading to …

General-purpose GPU-based systems are highly attractive, as they give potentially massive
performance at little cost. Realizing such potential is challenging due to the complexity of …

Unquestionably computer architectures have undergone a recent and noteworthy paradigm
shift that now delivers multi-and many-core systems with tens to many thousands of …

It has been widely shown that high-throughput computing architectures such as GPUs offer
large performance gains compared with their traditional low-latency counterparts for many …