MNSIM version1.1 ReadMe
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---------------------------------Update Information--------------------------------------
- Update the input parameters settings.
- Fix several bugs.
----------------------------------Running MNSIM------------------------------------------
-
Windows / MacOS: Create a project with all of the source files, set simulation configuration file (sim-config) and output results file address in argv[]; Linux: Build the project with $ make. If no sim-config and result files are specified, MNSIM will load the default (SimConfig.txt and result.txt), run MNSIM with $ ./MNSIM. If users specify their own configurations / result file by passing the ".txt" argument:$ ./MNSIM .txt .txt
-
Input Parameters Setting (MNSIM version 1.1):
Config part:
Simulation_Level: Estimation
Target_Outputs: Area/Latency/Power/Energy (Optimization Targets)
Application: CNN or BNN
Application_Scale: Number of Layers (conv + fully-connected)
Weight_Polarity: 2
Cell_Type: 1T1R
RRAM_Model: ideal
RRAM_Bit_Levels: 8
Transistor_Tech(nm): 130
Min_Crossbar_Size & Max_Crossbar_Size: 2^k, MNSIM will find the optimal design
Max_Crossbar_Size 1024
Write_Method: ideal
Line_Tech:[18,22,28,36,45,65,90]
Action_Type: Calculation
Pipeline: 0-not pipelined, 1-pipelined
Network part:
#: Layer number, from 1 to Application_Scale
Convolutional Layer:
Layer# {
Name Conv
Inputsize: input feature map size
Outputsize: output feature map size
Kernelsize
Stride
Inputchannel
Outputchannel
}
Fully-connected Layer:
Layer# {
Name FC
Inputlength
Outputlength
}
- Unit of the outputs: area: m^2, energy: J, power: W, latency: s.
----------------------------------Future Work and Update---------------------------------
- Support for different cell types: 0T1R and 1T1R
- Support for different bit levels of RRAM
- Add accuracy simulation of matrix-vector multiplications and CNN
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MNSIM version1.1 is only a test version. If you have any questions and suggestions about MNSIM please contact us via email.
Lixue Xia: [email protected] Zhenhua Zhu: [email protected]