A preliminary investigation of a neocortex model implementation on the Cray XD1

In this paper we study the acceleration of a new class of cognitive processing applications based on the structure of the neocortex. Specifically we examine the speedup of a visual cortex model for image recognition. We propose techniques to accelerate the application on general purpose processors and on reconfigurable logic. We present implementations of our approach on a Cray XD1 and compare the performance potential of scaling the design utilizing reconfigurable logic based acceleration to a software only design. Our results indicate that acceleration using reconfigurable logic can provide a significant speedup over a software only implementation.

[1]  Anders Lansner,et al.  Non-commercial Research and Educational Use including without Limitation Use in Instruction at Your Institution, Sending It to Specific Colleagues That You Know, and Providing a Copy to Your Institution's Administrator. All Other Uses, Reproduction and Distribution, including without Limitation Comm , 2022 .

[2]  J. Hawkins,et al.  On Intelligence , 2004 .

[3]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[4]  James A. Anderson,et al.  Programming a Parallel Computer: The Ersatz Brain Project , 2007, Challenges for Computational Intelligence.

[5]  Thomas Dean,et al.  A Computational Model of the Cerebral Cortex , 2005, AAAI.

[6]  James A. Anderson,et al.  Arithmetic on a Parallel Computer: Perception Versus Logic , 2003 .

[7]  D. George,et al.  Hierarchical Temporal Memory Concepts , Theory , and Terminology , 2006 .

[8]  D. George,et al.  A hierarchical Bayesian model of invariant pattern recognition in the visual cortex , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

[9]  D. Hammerstrom Artificial neural networks, where do we go next? , 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

[10]  Richard S. Zemel,et al.  Cortical Belief Networks , 2003, Computational Models for Neuroscience.

[11]  D. J. Felleman,et al.  Distributed hierarchical processing in the primate cerebral cortex. , 1991, Cerebral cortex.

[12]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems , 1988 .

[13]  Tai Sing Lee,et al.  Hierarchical Bayesian inference in the visual cortex. , 2003, Journal of the Optical Society of America. A, Optics, image science, and vision.

[14]  Tarek Taha,et al.  Feasibility of Hardware Acceleration of a Neocortex Model , 2007, ERSA.