gpu implementation
GPU Implementation of Parallel SVM as Applied to Intrusion Detection System
... Proposed methodology uses parallel SVM algorithm which divides large dataset into smaller chunks to be processed in parallel. It uses layered approach towards processing such large datasets where only support vectors ...
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Communication Optimization for Multi GPU Implementation of Smith Waterman Algorithm
... CUDA implementation of this algorithm speeds up the process of sequence matching in the protein ...multi-GPU implementation gives better performance than single GPU ...DyManD ...
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A streaming multi-GPU implementation of image simulation algorithms for scanning transmission electron microscopy
... multi-GPU implementation of the PRISM and mul- tislice algorithms for image formation in scanning transmission electron ...a GPU worksta- tion without the need for a computer ...
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Parallel GPU Implementation of ƞT Pairing over Fields of Characteristic Two
... We achieved timing per pairing of 12.7ms per pairing using GPU Tesla K20c which the core clock is 706 MHz. In regard to security level for new DLP algorithm, we took the extension degree of base field 𝑚 = 487 that ...
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A GPU Implementation of the Inverse Fast Multipole Method for Multi-Bistatic Imaging Applications
... IFMM implementation, there is an important difference mainly due to the kind of problem (forward/inverse) where these acceleration schemes are ...simplifies GPU implementation of IFMM, as it will be ...
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Estimating Gaussian Mixture Autoregressive model with Sequential Monte Carlo algorithm: A parallel GPU implementation
... Estimating Gaussian Mixture Autoregressive model with Sequential Monte Carlo algorithm: A parallel GPU implementation Yin, Ming University of Helsinki, Helsinki Center of Economic Resear[r] ...
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GPU implementation of partial order reduction
... GPUexplore is a model checker that can check for deadlocks and safety properties. GPUexplore executes all the computations on the GPU and does not rely on any processing by the CPU. The main kernel of GPUexplore ...
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GPU Implementation of Parallel Support Vector Machine Algorithm with Applications to Intruder Detection
... In our experiment, the CPU is Intel Pentium dual-core E5500 with a frequency of 2.80GHz. The GPU is NVIDIA GeForce GTS 250.The memory capacity is 512 MB, the number of multiprocessors is 16, the number of cores ...
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Parallel Implementation for Phase Field Simulation of Flow Effect on Dendritic Growth with GPU Acceleration
... a GPU with CUDA programming. The GPU implementation of the Sola-phase fi eld model is introduced in this ...GTX780 GPU with different memories are also ...the GPU computation with the ...
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Particle filter track before detect implementation on GPU
... Obviously, the operations in Figure 3 are complex. From algorithm aspect, Torstensson and Trieb [19] have made a research on different size of likelihood ratio areas in radar application. Its scheme is to use small ...
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GPU-based Implementation of Discrete Element Method for Simulation of the Geological Fault Geometry and Position
... The initial assignment of the particles to the lattices is performed by a sequential code by CPU. It is implemented particle-by-particle so that we determine the lattice number for considered particle and add the ...
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Mobile GPU-based implementation of automatic analysis method for long-term ECG
... OpenCL is a common multi-CPU/multi-GPU heterogeneous computing framework. OpenCL uses heterogeneous CPU/GPU hardwares to perform large-scale computa- tion tasks, especially tasks with high parallelism, more ...
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Parallel Implementation of the Max Min Ant System for the Travelling Salesman Problem on GPU
... MMAS sequentially is implemented on the above given hardware specification with a randomly generated graph with different no. of nodes as well as some standard graphs to compare our results. Comparative analysis of the ...
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An MPI-CUDA Implementation for Massively Parallel Incompressible Flow Computations on Multi-GPU Clusters
... CUDA is the software and hardware architecture for GPUs produced by NVIDIA. The Tesla series of computing servers are distinguished by their large memory (1.5GB in the older C870 model, 4GB in the latest C1060 model, 6GB ...
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Study of Parallel Image Processing with the Implementation of vHGW Algorithm using CUDA on NVIDIA’S GPU Framework
... the implementation of parallel image processing techniques using CUDA on NVIDIA GPU ...NVidia’s GPU GeForce GTX ...NVidia’s GPU GeForce GTX 860M and got significant results in terms of ...
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GPU Computing
... Environmental science is a multi disciplinary area, which includes several domains like rain- forest deforestation, agriculture, pollution con- trol, natural resource management, global warm- ing, soil contamination, ...
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Implementation of Multipattern String Matching Accelerated with GPU for Intrusion Detection System
... executes GPU specific instructions for Multi Pattern String Matching inspection based on the packets received and transfer the packets to ...on GPU is performed using Parallel Failureless Aho-Corasick ...
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A holistic scalable implementation approach of the lattice Boltzmann method for CPU/GPU heterogeneous clusters
... The GPU kernels are written in ...and GPU kernels implement the same functionality, but CUDA is favored due to its better availability in large-scale CPU/GPU clusters, its superior support by NVIDIA, ...
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GPU-based implementation of real-time system for spiking neural networks
... A spiking neural network is a model of a real biological neural network. A building block of an SNN is a mathematical model of a neuron. The choice of this model is design-specific. Neurons communicate with each other by ...
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A DIFFERENTIAL EVOLUTION ALGORITHM PARALLEL IMPLEMENTATION IN A GPU
... federal government standard on May 26, 2002 following the approval of the Secretary of Commerce. Also, AES is available in many various encryption formats, and is the first open cipher source that is publicly accessible ...
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