The Experts below are selected from a list of 9 Experts worldwide ranked by ideXlab platform

Joan Cabestany - One of the best experts on this subject based on the ideXlab platform.

  • a Coprocessor Card for fast neural network emulation
    International Work-Conference on Artificial and Natural Neural Networks, 1995
    Co-Authors: F Castillo, Jose Amparo Rodriguez Garcia, Juan Manuel Moreno, Joan Cabestany
    Abstract:

    In this article we present a Coprocessor Card for PC, designed for the fast emulation of neural network-based systems. The Card is composed of 6 custom neural processors arranged using a special parallel architecture. The processor is briefly presented and the structure of the Card discussed, along with the architecture's basics. Also presented are the software tools developed around the Card, the graphical interface used for drawing the net and the compiler used to translate the drawing into a series of instructions understood by the processor. Last, we present some results regarding a sample application in which the Card was tried: in the control of an inverted pendulum.

F Castillo - One of the best experts on this subject based on the ideXlab platform.

  • a Coprocessor Card for fast neural network emulation
    International Work-Conference on Artificial and Natural Neural Networks, 1995
    Co-Authors: F Castillo, Jose Amparo Rodriguez Garcia, Juan Manuel Moreno, Joan Cabestany
    Abstract:

    In this article we present a Coprocessor Card for PC, designed for the fast emulation of neural network-based systems. The Card is composed of 6 custom neural processors arranged using a special parallel architecture. The processor is briefly presented and the structure of the Card discussed, along with the architecture's basics. Also presented are the software tools developed around the Card, the graphical interface used for drawing the net and the compiler used to translate the drawing into a series of instructions understood by the processor. Last, we present some results regarding a sample application in which the Card was tried: in the control of an inverted pendulum.

Jose Amparo Rodriguez Garcia - One of the best experts on this subject based on the ideXlab platform.

  • a Coprocessor Card for fast neural network emulation
    International Work-Conference on Artificial and Natural Neural Networks, 1995
    Co-Authors: F Castillo, Jose Amparo Rodriguez Garcia, Juan Manuel Moreno, Joan Cabestany
    Abstract:

    In this article we present a Coprocessor Card for PC, designed for the fast emulation of neural network-based systems. The Card is composed of 6 custom neural processors arranged using a special parallel architecture. The processor is briefly presented and the structure of the Card discussed, along with the architecture's basics. Also presented are the software tools developed around the Card, the graphical interface used for drawing the net and the compiler used to translate the drawing into a series of instructions understood by the processor. Last, we present some results regarding a sample application in which the Card was tried: in the control of an inverted pendulum.

Juan Manuel Moreno - One of the best experts on this subject based on the ideXlab platform.

  • a Coprocessor Card for fast neural network emulation
    International Work-Conference on Artificial and Natural Neural Networks, 1995
    Co-Authors: F Castillo, Jose Amparo Rodriguez Garcia, Juan Manuel Moreno, Joan Cabestany
    Abstract:

    In this article we present a Coprocessor Card for PC, designed for the fast emulation of neural network-based systems. The Card is composed of 6 custom neural processors arranged using a special parallel architecture. The processor is briefly presented and the structure of the Card discussed, along with the architecture's basics. Also presented are the software tools developed around the Card, the graphical interface used for drawing the net and the compiler used to translate the drawing into a series of instructions understood by the processor. Last, we present some results regarding a sample application in which the Card was tried: in the control of an inverted pendulum.

Christoph Hagleitner - One of the best experts on this subject based on the ideXlab platform.

  • Measuring and Modeling the Power Consumption of Energy-Efficient FPGA Coprocessors for GEMM and FFT
    Journal of Signal Processing Systems, 2016
    Co-Authors: Heiner Giefers, Raphael Polig, Christoph Hagleitner
    Abstract:

    In this paper we analyze the power consumption and energy efficiency of general matrix-matrix multiplication (GEMM) and Fast Fourier Transform (FFT) implemented as streaming applications for an FPGA-based Coprocessor Card. The power consumption is measured with internal voltage sensors and the power draw is broken down onto the systems components in order to classify the energy consumed by the processor cores, the memory, the I/O links and the FPGA Card. We present an abstract model that allows for estimating the power consumption of FPGA accelerators on the system level and validate the model using the measured kernels. The performance and energy consumption is compared against optimized multi-threaded software running on the POWER7 host CPUs. Our experimental results show that the accelerator can improve the energy efficiency by an order of magnitude when the computations can be undertaken in a fixed point format. Using floating point data, the gain in energy-efficiency was measured as up to 30 % for the double precision GEMM accelerator and up to 5 × for a 1k complex FFT.