1. The Ovonic Cognitive Computer A New Paradigm
Stanford R. Ovshinsky
Energy Conversion Devices, Inc.
Rochester Hills, MI (USA)
Keynote Presentation
EPCOS 2004
Balzers - Principality of Liechtenstein
September 6, 2004

2. Introduction “The essence of life is information.” - Paul Davies
The ability of neurons through their synapses to have memory, learn, adapt and evolve in response to their environment is what neurophysiologists call plasticity.
Both optical and electrical Ovonic devices have plasticity and therefore open a huge new field of chalcogenide- based intelligent computers having intelligence that works in a similar manner to the brain.
I will explain how Ovonic devices make this possible.

3. Plasticity in Ovonic Chalcogenides
Plasticity is the ability of a biological material or its non-biological analog to be able to adapt or change in response to incoming energy signals so as to enable learning, decision making and other characteristics of intelligence as well as storage of learned information. The resulting changes are structural in nature very much like electrical or optical signals can make for conformal and configurational alterations in the amorphous phase of the Ovonic Phase Change Devices.
A single Ovonic device is capable of synaptic function
receiving and weighting multiple inputs
threshold activation
accumulates input energy signals without responding until the total accumulated energy reaches a threshold level and then the device changes from a high to a low resistance state in a process that mimics the firing of a biological neuron.
Individual Ovonic devices can be readily interconnected
Highly dense two-dimensional arrays
Three-dimensional, vertically integrated networks
The threshold level of individual Ovonic devices can be controlled by various means
The Ovonic Quantum Control Device
The plasticity of the Ovonic neurosynaptic arrays opens up possibilities of unifying software and hardware.

4. Ovonic Universal Memory Device (OUM)
The figure shows the relationship between the programming current and the programmed resistance of a standard Ovonic semiconductor memory device.
A 50 ns, 1.5 mA pulse will cause the resistance to be high. When 50 ns pulses of increasing amplitude are applied to the device, no change is observed until at about 0.8 mA when the device crystallizes, and low resistance is achieved.
amorphous
crystalline

5. Ovonic Electrical Multi-State Data Storage Programming Voltage (V)
When the amplitude of the pulses is changed in small increments, intermediate resistance states can be achieved.
This programming mode is direct overwrite.
The 16 resistance levels shown in the top figure correspond to storage of four bits in a single device.
The data shows repeatability over 1600 programming events. The test was stopped without failure
The bottom graph shows binary cycling performance. The test was stopped without failure. Continued testing to 1014 would have taken another year.
Device Resistance (W)
Multiple-bit storage in each memory cell (Ten pulses per step, repeated ten times)
Programming Voltage (V)

6. Operation of Ovonic Cognitive Device
Various pulsing protocols are used depending upon the nature of the task performed

7. Ovonic Cognitive Device Operation
Device resistance remains high after each pre-threshold pulse.
Once the threshold is exceeded, the resistance drops dramatically.
Different pulse widths can be selected to change the number of pulses used to fire the device.
The graph shows consistency over 1,000 “cycles.” The test was stopped without failure.

8. Functional Model of the Ovonic Cognitive Device

9. The Optical Ovonic Cognitive Effect
Increased storage density in an Ovonic phase change optical disk can be achieved using intermediate reflectivity states. This data shows how step-wise changes in pulse width can lead to step-wise changes in reflectivity, just as step-wise increments in the electrical device give step-wise changes in resistance.
Beyond multi-state storage, this data shows how pre-threshold synaptic inputs (in this case, seven optical pulses) accumulate information before the first change in reflectivity can be seen when the threshold is exceeded.

10. Structure of Nerve Cells and their Interconnections
Diagram of a biological nerve cell showing synapses and synaptic contacts
Simplified schematic of the communication of information between neurons
Nerve Cell
input
output
axon
synapse
Afferent nerve terminal
Node of Ranvier
Myelin sheath
Axon process
Cell body
Synapse
Dendrite
Synaptic contact
S. Dehaene: “The new findings in numerical neuroscience compel us to accept that our mathematics, sometimes heralded as the pinnacle of human activity, is really made possible by conceptual foundations laid down long ago by evolution and rooted in our primate brain. We are clearly not the only species with a knack for numbers.”
B. Katz: “Each nerve cell, in a way, is a nervous system in miniature.”

11. I-V Curves of OTS and OQCD
Voltage
Current
The Ovonic Threshold Switch (schematic IV curve at right) has high conductivity when switched on, due to a solid state plasma not seen before. It switches off by plasma recombination. The current capacity is 3x108A/cm2, 30 times higher than CMOS transistors.
The Ovonic Quantum Control Device expands the capabilities of Ovonic Threshold switches by adding control terminals and can replace transistors as well as adding new functionalities, and offering new degrees of freedom to the design of computer architecture.
Application of a control voltage changes both the threshold voltage and the holding current, providing two forms of control and modulation in an Ovonic Threshold Switch.

12. The Ovonic Cognitive Computer
Conventional Silicon Computers
Each Element:
Computes based on
single bit (binary)
manipulation
Manipulates data
sequentially,
bit by bit
Ovonic Cognitive Computer
Manipulates, processes and stores information in a non-
volatile radiation hard and multilevel manner
Hardware and software are unified
Low voltage and low current operation
Performs arithmetic operations (+,-,x, ) on multi-bit numbers
(0,1,2,3…n)
Performs modular arithmetic
Combines logic and memory in a single device
Executes multi-valued logic
Stores the result in a non-volatile manner
Simple, powerful encryption
Acts as a neurosynaptic cell; i.e. possesses intelligence
capability
Scales down to angstrom scale dimensions; huge density
Device speed in the picosecond range
Capable of massive parallelism; also addressing different values

13. The Ovonic Cognitive Computer
Arrays of computation and storage elements are combined in a conventional computer which:
Requires separate storage
and processor units or regions
Has limited parallel processing
capability
Is limited to Von Neumann
operations
An array of Ovonic elements
Easily factors large numbers
Has attributes of proposed quantum computers without their
limitations, such as analogs of quantum entanglement and
coherence at practical conditions and environments
Performs high level mathematical functions (e.g. vector and
array processing)
Has high 3-dimensional interconnectivity, huge density,
giving rise to high speed, hyper-parallel processing (i.e.
millions of interconnected processors)
Interconnectivity is simply and inherently reconfigurable
Has adaptive learning capability
The Ovonic Devices are:
Mass produced in exceptionally dense, all thin film, uniquely
interconnected arrays
Mass manufactured as a thin film, flexible device using
proven technologies
Ovonic Quantum Control Device - unique, high speed, low
cost 3 or more terminal device. Nanostructure capable of
carrying large current density

14. Closing
“…it seems good for philosophers to move to new ways and systems; good for them to allow neither the voice of the detractor, nor the weight of ancient culture, nor the fullness of authority to deter those who would declare their own views. In that way each age produces their own crop of authors and arts.”
Fernel, 16th century.