The RAP: a ring array processor for layered network calculations

The authors have designed and implemented a ring array processor, RAP, for fast implementation of layered neural network algorithms. The RAP is a multi-DSP system targeted at continuous speech recognition using connectionist algorithms. Four boards, each with four Texas Instruments, TMS 320C30 DSPs, serve as an array processor for a 68020-based host running a real-time operating system. The overall system is controlled from a Sun workstation via the Ethernet. Each board includes 16 MB of dynamic memory (expandable to 64 MB) and 1 MB of fast static RAM. Theoretical peak performance is 128 MFLOPS/board, and test runs with the first working board show a sustained throughput of roughly one-third to one-half of this for algorithms of interest. Software development is aided by a Sun workstation-based command interpreter, tools from the standard C environment and a library of matrix and vector routines.<<ETX>>

[1]  Robert W. Brodersen,et al.  An integrated-circuit-based speech recognition system , 1986, IEEE Trans. Acoust. Speech Signal Process..

[2]  H. T. Kung,et al.  Using warp as a supercomputer in signal processing , 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[3]  Mark A. Fanty,et al.  Computing with structured connectionist networks , 1988, CACM.

[4]  D. S. Touretzky,et al.  Neural network simulation at Warp speed: how we got 17 million connections per second , 1988, IEEE 1988 International Conference on Neural Networks.

[5]  A. Iwata,et al.  An artificial neural network accelerator using general purpose 24 bit floating point digital signal processors , 1989, International 1989 Joint Conference on Neural Networks.

[6]  Hervé Bourlard,et al.  Generalization and Parameter Estimation in Feedforward Netws: Some Experiments , 1989, NIPS.

[7]  Hervé Bourlard,et al.  Statistical Inference in Multilayer Perceptrons and Hidden Markov Models with Applications in Continuous Speech Recognition , 1989, NATO Neurocomputing.

[8]  Jenq-Neng Hwang,et al.  A Unified Systolic Architecture for Artificial Neural Networks , 1989, J. Parallel Distributed Comput..

[9]  Jan M. Rabaey,et al.  A large-vocabulary real-time continuous-speech recognition system , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[10]  Jill P. Mesirov,et al.  An Efficient Implementation of the Back-propagation Algorithm on the Connection Machine CM-2 , 1989, NIPS.

[11]  Yann LeCun,et al.  Optimal Brain Damage , 1989, NIPS.

[12]  R. Bisiani,et al.  BEAM. An accelerator for speech recognition , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[13]  Hervé Bourlard,et al.  Continuous speech recognition using multilayer perceptrons with hidden Markov models , 1990, International Conference on Acoustics, Speech, and Signal Processing.