12. Revision History ............................................................. 18
Appendix A. Dimension ........................................................... 19
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NeuroPi H/W User Guide
1. Introduction
This guide describes how to use the NeuroPi easy-to-use on Raspberry Pi for evaluation user application with
neuromorphic device called NM500; which has 576 neurons and has 256bytes memory and hard-wired logic per
each neuron to achieve functions mainly required in user application. (NeuroPi has two NM500) Along with this
board it begins to evaluate user application such as pattern matching, machine learning using NM500 with
provided software development environment.
It targets for Raspberry Pi series.
The contents of this guide include features, hardware components and specs, register map, and a complete set
of block diagram of the NeuroPi.
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2. Features
The NeuroPi includes;
Two neuromorphic devices in 64pin WLCSP package
40 pin header GPIO connector to be compatible with Raspberry Pi
Support SPI interface for communication with Raspberry Pi
Preloaded FPGA for interface logic
Figure 2.1 shows the top/bottom side of the NeuroPi
Figure 2.1 The NeuroPi (Top/Bottom side)
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The NeuroPi consist of two detachable simple boards; module board and main board
Module board – This board features the following on-board components and circuits
Detachable connector for Main board
Two NM500 (neuromorphic device)
FPGA for interface logic
Power components
Figure 2.2 shows the top/bottom side of the module board
Figure 2.2 Module board of NeuroPi (Top/Bottom side)
Main board – This board has physically making connection with Raspberry Pi and the module board has mounted
on this board
40-pins header GPIO connector for Raspberry Pi
Attachable connector for the module board
Figure 2.3 shows the top/bottom side of the main board
Figure 2.3 Main board of NeuroPi (Top/Bottom side)
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3. Function Block Diagram
The NeuroPi allows user can evaluate a pattern matching application using NM500 with Raspberry Pi.
If additional sensors are needed for pattern matching, user can use the 40-pin header connector on the NeuroPi
through go to Raspberry Pi.
Raspberry Pi can access NM500(neuromorphic device) on the NeuroPi via SPI interface, FPGA on the NeuroPi
can make an interface bridge to achieve between Raspberry Pi(SPI) and NM500(NMBus) as below block diagram.
Figure 3.1 shows a block diagram of the NeuroPi
Figure 3.1 Block diagram of NeuroPi
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4. NM500 device
A nepes neuromorphic semiconductor chip (named NM500) is a fully parallel silicon neural network device. It is
a chain of identical elements (i.e. neurons) addressed in parallel. In addition, the neurons fully collaborate with
each other through a bi-directional and parallel neuron bus which is the key to accuracy, adaptively and speed
performance.
The NM500 device is composed of the following three blocks:
Neuron Interconnect block for NMbus*
Neuron block
Chain of neurons, daisy-chained and interconnected block
* NMbus is a main interface of NM500 device, as like SRAM interface.
And those neurons can learn and recognize input vectors autonomously and in parallel using internal own
classification algorithm logic and memory blocks
For more detail information, please visit a following link: http://www.theneuromorphic.com/nm500/
Figure 4.1 shows blocks of NM500 device
Figure 4.1 Blocks of NM500
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5. Interfaces
NeuroPi provides SPI Interface in order to communicate with Raspberry Pi.
40 Pin Header GPIO Connector – NeuroPi provides a GPIO connector which is compatible with Raspberry Pi
and it has general interface such as UART, SPI, I2C, GPIO with 3.3V power source.
Among the various interfaces supported by Raspberry Pi, you need to use the SPI0 on the GPIO connector to
use NeuroPi.
For NeuroPi SPI Interface supports up to 15 Mhz now.
Figure 5.1 shows a pin map of GPIO Connector, including SPI interface on the NeuroPi
Figure 5.1 SPI interface on the 40 pin header GPIO connector
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6. SDK (Software Development Kit)
Raspberry Pi platform, to support it can be used following SDK. And you can download it on following link.