Hardware constraints

While working with CNN2SNN and the Akida simulator, only few limitations are imposed. When mapping a model to the Akida hardware, not all Model and Layer configurations are supported.

When dealing with an unsupported model, one can call the dedicated Akida helper that will try to find workarounds for incompatibilities and build a converted model:

import akida.compatibility
updated_model = akida.compatibility.create_from_model(incompatible_model)

InputConvolutional

Input	Width	Height	Channels
Dimensions	[5:256]	>= 5	1, 3

Convolutions	Kernel Size	Stride	Type
Parameters	3×3, 5×5, 7×7	1, 2, 3	Same, Valid

Filters	3x3	5x5	7x7
Max(1 ch)	512	192	96
Max(3 ch)	192	64	32

Max Pooling	Size
Parameters	1x1, 1×2, 2×1, 2×2

Note

• pool_stride is equal to pool_size for InputConvolutional

Quantization	Input	Weights	Activation
Bitwidth	8	1, 2, 4, 8	1, 2, 4

Convolutional

Convolutions	Kernel Size	Stride	Type
Parameters	1x1, 3×3, 5×5, 7×7	1, 2	Same

Note

• stride 2 is only supported with 3x3 kernels

Max Pooling	Size	Stride
Parameters	1x1, 2×2	1, 2

Note

• pooling stride cannot be greater than pooling size

• a layer with max pooling must be followed by another Convolutional or SeparableConvolutional layer.

Global Average Pooling	Width
Dimensions	[1:32]

Note

• with global average pooling the output of the convolution must have at least 3 rows.

Quantization	Input	Weights	Activation
Bitwidth	1, 2, 4	1, 2, 4	1, 2, 4

SeparableConvolutional

Convolutions	Kernel Size	Stride	Type
Parameters	3×3, 5×5, 7×7	1, 2	Same

Note

• stride 2 is only supported with 3x3 kernels

Max Pooling	Size	Stride
Parameters	1x1, 2×2	1, 2

Note

• pooling stride cannot be greater than pooling size.

• a layer with max pooling must be followed by another Convolutional or SeparableConvolutional layer.

Global Average Pooling	Width
Dimensions	[1:32]

Note

With global average pooling:

• the output of the convolution must have at least 3 rows

• 1x1 inputs are not supported

Quantization	Input	Weights	Activation
Bitwidth	1, 2, 4	2, 4	1, 2, 4

FullyConnected

Input	Width	Height	WxHxC
Dimensions	1	1	<= 57334

Quantization	Input	Weights	Activation
Bitwidth	1, 2, 4	1, 2, 4	1, 2, 4