Neural network chips for trigger purposes in high energy physics

Conference · Tue Dec 31 04:00:00 EST 1996

OSTI ID:512991

Gemmeke, H; Eppler, W; Fischer, T ^[1]

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1. Research Center Karlsruhe (Germany); and others

Two novel neural chips SAND (Simple Applicable Neural Device) and SIOP (Serial Input - Operating Parallel) are described. Both are highly usable for hardware triggers in particle physics. The chips are optimized for a high input data rate at a very low cost basis. The performance of a single SAND chip is 200 MOPS due to four parallel 16 bit multipliers and 40 bit adders working in one clock cycle. The chip is able to implement feedforward neural networks, Kohonen feature maps and radial basis function networks. Four chips will be implemented on a PCI-board for simulation and on a VUE board for trigger and on- and off-line analysis. For small sized feedforward neural networks the bit-serial neuro-chip SIOP may lead to even smaller latencies because each synaptic connection is implemented by its own bit serial multiplier and adder.

• OSTI ID: 512991
• Report Number(s): CONF-961123--
• Country of Publication: United States
• Language: English

Related Subjects

43 PARTICLE ACCELERATORS
99 GENERAL AND MISCELLANEOUS
COMPUTER ARCHITECTURE
NEURAL NETWORKS
PERFORMANCE
TRIGGER CIRCUITS