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All the baseband signal processing is implemented on Lyrtech SignalWAVe DSP/FPGA development boards.
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Preliminary data processing is implemented for each record.
Data processing is implemented as a distributed process run on a computing cluster with 192 processor dual-dual core 2.8 Ghz computer nodes.
Parallel processing is implemented using OpenMP for multithread computing on a multicore CPU and NVIDIA CUDA for general-purpose computing on GPUs (GPGPU).
An important trend is work designed to shed light on how sentence processing is implemented in the brain.
LRE quantification does not rely on user-supplied standards and, if automated data processing is implemented, requires little or no training beyond that required for preparing amplification reactions.
The entire processing pipeline is implemented on the latest GPU to significantly speed up the processing.
In this study, a set of four image processing application tasks is implemented on eight different SIMD configurations.
The FPGA processing pipeline described above is implemented on a PCI Express FPGA board that is equipped with external memory banks.
In this paper, we propose to solve this challenge with a fast 3D B-spline pseudo-inversion algorithm that is implemented on graphics processing unit (GPU).
For speed, the algorithm is implemented on Graphics Processing Unit (GPU) architecture, resulting in analysis times on the order of minutes.
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