SUPS
In computational neuroscience, SUPS (for Synaptic Updates Per Second) or formerly CUPS (Connections Updates Per Second) is a measure of a neuronal network performance, useful in fields of neuroscience, cognitive science, artificial intelligence, and computer science.
Computing
For a processor or computer designed to simulate a neural network SUPS is measured as the product of simulated neurons and average connectivity (synapses) per neuron per second:
Depending on the type of simulation it is usually equal to the total number of synapses simulated.
In an "asynchronous" dynamic simulation if a neuron spikes at Hz, the average rate of synaptic updates provoked by the activity of that neuron is . In a synchronous simulation with step the number of synaptic updates per second would be . As has to be chosen much smaller than the average interval between two successive afferent spikes, which implies , giving an average of synaptic updates equal to . Therefore, spike-driven synaptic dynamics leads to a linear scaling of computational complexity O(N) per neuron, compared with the O(N2) in the "synchronous" case.[1]
Records
Developed in the 1980s Adaptive Solutions' CNAPS-1064 Digital Parallel Processor chip is a full
After the presentation of the RN-100 (12 MHz) single neuron chip at Seattle 1991 Ricoh developed the multi-neuron chip RN-200. It had 16 neurons and 16 synapses per neuron. The chip has on-chip learning ability using a proprietary backdrop algorithm. It came in a 257-pin PGA encapsulation and drew 3.0 W at a maximum. It was capable of 3 GCPS (1 GCPS at 32 MHz). [3]
In 1991–97,
In 2013, the K computer was used to simulate a neural network of 1.73 billion neurons with a total of 10.4 trillion synapses (1% of the human brain). The simulation ran for 40 minutes to simulate 1 s of brain activity at a normal activity level (4.4 on average). The simulation required 1 Petabyte of storage.[5]
See also
- FLOP
- SPECint
- SPECfp
- Multiply–accumulate operation
- Orders of magnitude (computing)
- SyNAPSE
References
- ISBN 978-3-540-76263-8.
- ^ Real-Time Computing: Implications for General Microprocessors Chip Weems, Steve Dropsho
- ISBN 9780080440101.
- ^ Neural Network Hardware Clark S. Lindsey, Bruce Denby, Thomas Lindblad, 1998
- ^ Fujitsu supercomputer simulates 1 second of brain activity Tim Hornyak, CNET, August 5, 2013