Tag: CPU
Intel Xeon Phi Coprocessor Infographic
To complement announcement of Xeon Phi Coprocessor Intel posted fantastic infographic.
Intel announces Xeon Phi coprocessor based on Many Integrated Core (Intel MIC) Architecture
Intel just announced its new brand for “Many Integrated Core Architecture” chips, Intel Xeon Phi, with the coprocessors for workstations, data centers and even supercomputers. Available by the end of 2012, the first generation of Intel Xeon Phi product family will complement the existing Intel Xeon.
A sparse octree gravitational N-body code that runs entirely on the GPU processor
We present the implementation and performance of a new gravitational N-body tree-code that is specifically designed for the graphics processing unit (GPU). All parts of the tree-code algorithm are executed on the GPU.
Computation of Induced Dipoles in Molecular Mechanics Simulations Using Graphics Processors
In this work, we present a tentative step toward the efficient implementation of polarizable molecular mechanics force fields with GPU acceleration.
Realtime Computer Vision with OpenCV
OpenCV have made it easier for application developers to use computer vision. They are well-documented and vibrant open source projects that keep growing, and they are being adapted to new computing technologies
High-performance computing tools for the integrated assessment and modelling of social-ecological systems
Integrated spatio-temporal assessment and modelling of complex social–ecological systems is required to address global environmental challenges.
Accelerating finite difference wavefield-continuation depth migration by GPU
We introduce a new hardware architecture, based on which the finite difference wavefield-continuation depth migration can be conducted using the GPU as a CPU coprocessor.
CUDA-MPI-FDTD implementation of Maxwell’s equations in general dispersive media
We present the first MPI-CUDA implementation of Finite-Difference Time-Domain (FDTD) discretization of Maxwell’s equations in dispersive media that uses the MPI API to assign each CPU node its share of the computational domain and GPUs to their corresponding CPU threads
Language identification using multi-core processors
We explore the application of GPUs to speech pattern processing, using language identification (LID) to demonstrate their benefits. Realization of the full potential of GPUs requires both effective coding of predetermined algorithms, and, if there is a choice, selection of the algorithm or technique for a specific function that is most able to exploit the GPU
A Fair Comparison of Modern CPUs and GPUs Running the Genetic Algorithm under the Knapsack Benchmark
We show the performance comparison supported by architecture characteristics narrowing the performance gain of GPUs
