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high-performance parallel computing platform

A Parallel Flood Forecasting and Warning Platform Based on HPC Clusters

A Parallel Flood Forecasting and Warning Platform Based on HPC Clusters

... Parallel computing technology, cloud computing technology provides a good technical means for the construction of national or basin flash flood warning system to fine warning analysis (Shang, et ...

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Parallel Implementation of Fuzzy Clustering          Algorithm Based on MapReduce Computing Model
          of Hadoop –A Detailed Survey

Parallel Implementation of Fuzzy Clustering Algorithm Based on MapReduce Computing Model of Hadoop –A Detailed Survey

... CPU platform to improve the clustering ...capable parallel clustering algorithm in a top-performance cluster ...expensive high-performance ...

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Scalable parallel evolutionary optimisation based on high performance computing

Scalable parallel evolutionary optimisation based on high performance computing

... Therefore, high performance computing (HPC), which can scale to extensive computing resources, has become increasingly important in research and engineering fields in recent ...pay-as-you-go ...

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Semantic Network Array Processor as a Massively Parallel Computing Platform for High Performance and Large Scale Natural Language Processing

Semantic Network Array Processor as a Massively Parallel Computing Platform for High Performance and Large Scale Natural Language Processing

... Semantic Network Array Processor as a Massively Parallel Computing Platform for High Performance and Large Scale Natural Language Processing S e m a n t i c N e t w o r k A r r a y P r o c e s s o r a[.] ...

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HIGH PERFORMANCE INTEGRATION OF DATA PARALLEL FILE SYSTEMS AND COMPUTING: OPTIMIZING MAPREDUCE

HIGH PERFORMANCE INTEGRATION OF DATA PARALLEL FILE SYSTEMS AND COMPUTING: OPTIMIZING MAPREDUCE

... mitigate performance degradation. However the performance gain is obtained at the cost of duplicate processing and more resource ....NET platform was presented in ...

196

Research on High-performance and Scalable Data Access in Parallel Big Data Computing

Research on High-performance and Scalable Data Access in Parallel Big Data Computing

... the parallel I/O ...the performance gap between serving fragments and serving large ...the performance of parallel I/O ...a platform that realizes efficient data movement between ...

133

Impact of Process Allocation Strategies in High Performance Cloud Computing on Azure Platform

Impact of Process Allocation Strategies in High Performance Cloud Computing on Azure Platform

... major performance bottlenecks in HPC application running on Amazon EC2 Cluster Computing ...communication performance on ten gigabits Ethernet network and shared memory using Intel MPI Benchmarks ...

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Parallel Computing: High Performance

Parallel Computing: High Performance

... sequential performance and many small cores, optimized for throughput, for parallel workloads); even when designed to be similar, process variation will endow them with different performance ...

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CUDA: High Parallel Computing Performance

CUDA: High Parallel Computing Performance

... GPU computing, or the utilization of graphics processors for general-purpose computing, began in earnest many years ...CUDA platform changed that, providing a massively multithreaded general purpose ...

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Load Balancing & Task Scheduling Algorithms in Parallel Computing Environment: A Review

Load Balancing & Task Scheduling Algorithms in Parallel Computing Environment: A Review

... Authors directed their analysis towards rushing up the convergence of genetic algorithms by using multiple agents and completely different universe to schedule sets of tasks [15]. The utilization of multiple ab initio ...

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A 10 BIT 50 MS/S LOW POWER PIPELINE ADC FOR WIMAX/LTE

A 10 BIT 50 MS/S LOW POWER PIPELINE ADC FOR WIMAX/LTE

... scale high-performance scientific computing proposed by America’s six laboratories and two universities in ...in parallel mechanism, reflection, object-oriented semantic definition, and ...

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AN EVOLUTIONARY APPROACH TO PARALLEL COMPUTING USING GPU

AN EVOLUTIONARY APPROACH TO PARALLEL COMPUTING USING GPU

... absolute High performance computing. Simple data-parallel constructs, enabling the use of the GPU as a streaming ...a computing device compared to the Central processing Unit , to ...

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Performance Analysis of Fermat Factorization Algorithms

Performance Analysis of Fermat Factorization Algorithms

... The RSA cryptosystem includes two mathematical operations that are opposite to each other. The first operation is multiplication, which is easy to compute. The running time to compute the product of two numbers is 𝑂(𝑏 2 ...

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SCSP3133: High Performance Data Processing / SCSR3233: Hig. Performance & Parallel Computing. Module 2: Parallel Computers Architectures

SCSP3133: High Performance Data Processing / SCSR3233: Hig. Performance & Parallel Computing. Module 2: Parallel Computers Architectures

... Ismail Fauzi Isnin SCSP3133: High Performance Data Processing Direct topology 5 switch nodes 5 processor nodes Direct topology 16 switch nodes 16 processor nodes indirect topology 9 swit[r] ...

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Scalable Deep Analytics on Cloud and High Performance Computing Environments

Scalable Deep Analytics on Cloud and High Performance Computing Environments

... classic parallel algorithms as one uses large collective operations (reductions or broadcasts) rather than the many small messages familiar from parallel particle dynamics and partial differential equation ...

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Programming GPUs with CUDA

Programming GPUs with CUDA

... CUDA = Compute Unified Device Architecture • Software platform for parallel computing on Nvidia GPUs.. —introduced in 2006.[r] ...

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d2o: a distributed data object for parallel high-performance computing in Python

d2o: a distributed data object for parallel high-performance computing in Python

... DistArray [7] is very mature and powerful. Its approach is very similar to d2o: It mim- ics the interface of a multi dimensional numpy array while distributing the data among nodes in a cluster. However, DistArray ...

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Next Generation IoT and Data-based Grid

Next Generation IoT and Data-based Grid

... K-Means execution time on varying number of nodes with 20 processes in each node with 1 million points and 64000 centroids. Each point has 2 attributes. K-Means performed well on all three platforms when the computation ...

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Task based Parallel Computation of the Density Matrix in Quantum based Molecular Dynamics using Graph Partitioning

Task based Parallel Computation of the Density Matrix in Quantum based Molecular Dynamics using Graph Partitioning

... Figure 4 also shows that our CnC application is significantly more efficient than the Charm++ one in a shared-memory environment. Charm++ was developed for distributed memory using charm-MPI interoperability, while the ...

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Airborne radar clutter simulation using GPU
(CUDA)

Airborne radar clutter simulation using GPU (CUDA)

... For airborne radars clutter is one of the major performance limiters. The clutter returns enter the radar receiver either through the main lobe of antenna or through the side lobes. The portion of clutter power ...

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