ACE: a digital floating point CNN emulator engine

The architecture of ACE, a multiprocessor analogic cellular neural network (CNN) emulator engine consisting of 2 to 16 TMS320C40 floating point DSPs is introduced. The engine containing up to 512 Mbyte RAM (enough to store a 512/spl times/512/spl times/512 sized CNN cube) which can be controlled through its SCSI port. It can either accelerate the multilayer CNN simulator CNNM or be accessed directly from the high level, C-based analogic CNN language ACL to achieve the simulation speed of /spl sim/2.8 /spl mu/sec/cell/iteration/DSP for 3/spl times/3 linear templates.

[1]  Tamás Roska,et al.  The CNN universal machine: an analogic array computer , 1993 .

[2]  P. Szolgay,et al.  On a CNN chip-prototyping system , 1994, Proceedings of the Third IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA-94).

[3]  Lin-Bao Yang,et al.  Cellular neural networks: theory , 1988 .

[4]  P. Szolgay,et al.  Transient response computation of a mechanical vibrating system using cellular neural networks , 1994, Proceedings of the Third IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA-94).

[5]  Tamás Roska,et al.  A digital multiprocessor hardware accelerator board for cellular neural networks: CNN-HAC , 1992, Int. J. Circuit Theory Appl..