Comments (4)
Hi. This project is open-source. You're welcome to do a fork, modify it and use it in your research. Please cite us in that case.
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hey @Adrian-2105 i am beginner to his field and i have gone through your yt videos it was nice , so can you please help me out how to go through the your code base basically i need a road-map so that i can understand how marie is implemented on top of that i can build my accelerator
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I have attached the STONNE paper to this comment, so firstly I would recommend reading it: STONNE_Enabling_Cycle-Level_Microarchitectural_Simulation_for_DNN_Inference_Accelerators.pdf
I can also give you some upper-level introduction to the simulator source code, but you will need to spend time to understand and be able to work with it. The main file structure to simulate the MAERI architecture is:
main.cpp
: CLI input parsingSTONNEmodel.cpp
: main STONNE module where all the on-chip networks are created and configuredSDMemory.cpp
: memory controller of MAERI, the most important component since it orchestrates the data movement and executionDSNetwork.cpp
&DSNetworkTop.cpp
: distribution networkMSNetwork.cpp
: multiplier networkASNetwork.cpp
: reduction network
The rest of the files mainly focus on the simulation of other kinds of architecture, so you can only focus on the ones I mentioned. To get a deeper understanding of each part, you will need to navigate through the code.
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thanks a lot man
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Related Issues (20)
- stonne_connect compile fail when pytorch compilered with clang++ HOT 1
- `weights_tensorflow.pb` is in owner's trash HOT 4
- `NLP/BERT/` directory is missing HOT 3
- Missing building blocks of SIGMA HOT 2
- Error in installation of vision HOT 1
- Three questions about Utilization HOT 1
- Steps to Install STONNE successfully HOT 3
- Parameter stats_path='.' missing for the SimulatedConv2d HOT 2
- Python-frontend installation errors HOT 3
- Memory leaks during big simulation runs - Destructors not being called HOT 2
- Pytorch Frontend Install Error HOT 5
- Question about the 'simulated_matmul()' HOT 7
- Questions about list of simulated functions HOT 4
- Printing individual time breakup values for the Simulator HOT 3
- Can we implement training on STONNE? HOT 2
- DRAM modeling HOT 4
- STT-RAM Implementation HOT 2
- The unit of data and frequency of the stonne HOT 6
- PyTorch frontend HOT 1
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