Publication | Closed Access
A Deep Learning Prediction Process Accelerator Based FPGA
54
Citations
7
References
2015
Year
Unknown Venue
EngineeringMachine LearningHardware AccelerationEdge ComputingHardware AlgorithmComputer EngineeringComputer ArchitectureDeep Learning AcceleratorDomain-specific AcceleratorEmbedded Machine LearningParallel ProgrammingComputer ScienceData Access OptimizationParallel ComputingDeep LearningFpga Design
Recently, machine learning is widely used in applications and cloud services. And as the emerging field of machine learning, deep learning shows excellent ability in solving complex learning problems. To give users better experience, high performance implementations of deep learning applications seem very important. As a common means to accelerate algorithms, FPGA has high performance, low power consumption, small size and other characteristics. So we use FPGA to design a deep learning accelerator, the accelerator focuses on the implementation of the prediction process, data access optimization and pipeline structure. Compared with Core 2 CPU 2.3GHz, our accelerator can achieve promising result.
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