according to world health organization, breast cancer is one of the most deadly cancers occurred in women. therefore accurate diagnosis and prediction is important to decrease the high death rate. the aim of this paper is twofold. first, improving breast cancer detection accuracy using modified fuzzy logic (mfl) then improving the performance of mfl algorithm using gpu platform. the experimenta...

We present a GPU algorithm for the nearest neighbor search, an important database problem. The search is completely performed using the GPU: No further post-processing using the CPU is needed. Our experimental results, using large synthetic and real-world data sets, showed that our GPU algorithm is several times faster than its CPU version.

The ever increasing peak floating-point performance and memory bandwidth of GPUs is making them increasingly ubiquitous in the high performance computing community. With increasing adoption of GPUs in cluster environments, applications that cannot take advantage of this hardware will be at a distinct disadvantage. For the class of applications that can achieve massive speedups of 100x or more o...

SHARMA, SIDDHARTH. Parameter Estimation for System Biology Models on GPU Clusters . (Under the direction of Dr. James Tuck.) In this work, we consider the parallelization of interval based parameter estimation with uncertainty propagation for non-linear ODE models. This approach is especially important in systems biology research as it addresses the uncertainty often present in data recorded fr...

Glift is an abstraction and generic template library for parallel, random-access data structures on graphics processing units (GPUs). Glift simplifies the description of new and existing GPU data structures, stimulates development of complex GPU algorithms, performs equivalently to hand-coded implementations, and introduces a parallel iteration model for GPU computation.

Lately, programmers have started to take advantage of the GPU capabilities of their systems. Still, programming for the GPU can be very hard. We are trying to hide some of this complexity from the programmer by making the compiler automatically transform embarrassingly parallel loops to GPU kernels. To this end, we have implemented a compiler pass that transforms simple loops to OpenCL kernels.

Many research works have recently experimented with GPU to accelerate packet processing in network applications. Most works have shown that GPU brings a significant performance boost when it is compared to the CPUonly approach, thanks to its highly-parallel computation capacity and large memory bandwidth. However, a recent work argues that for many applications, the key enabler for high perform...

Recent years have witnessed tremendous growth for programmable graphics hardware (GPU), both in terms of performance and functionality. In this paper, we overview the high-level architecture of modern GPU, and introduce the GPU programming model. We also briefly describe the kinds the visual effects and applications that can be achieved by programmable graphics hardware.

We use the graphics processing unit (GPU) for fast calculations of helicity amplitudes of physics processes. As our first attempt, we compute uu → nγ (n=2 to 8) processes in pp collisions at √ s = 14TeV by transferring the MadGraph generated HELAS amplitudes (FORTRAN) into newly developed HEGET (HELAS Evaluation with GPU Enhanced Technology) codes written in CUDA, a C-platform developed by NVID...