Summary of Micsim: a Modular Simulator For Mixed-signal Compute-in-memory Based Ai Accelerator, by Cong Wang et al.
MICSim: A Modular Simulator for Mixed-signal Compute-in-Memory based AI Accelerator
by Cong Wang, Zeming Chen, Shanshi Huang
First submitted to arxiv on: 23 Sep 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Hardware Architecture (cs.AR)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed MICSim is an open-source pre-circuit simulator designed for evaluating the software performance and hardware overhead of mixed-signal compute-in-memory (CIM) accelerators in early stages. It features a modular design, enabling easy co-design, design space exploration, and extension to accommodate new designs. By building upon the state-of-the-art CIM simulator NeuroSim, MICSim provides a configurable simulation framework that supports various quantization algorithms, circuit/architecture designs, and memory devices. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary MICSim is a special computer program that helps designers make better chips for computers. It’s like a virtual test lab where they can try out different ideas before actually building the chip. This makes it easier to find the best combination of features that work well together. The program is based on another tool called NeuroSim, and it lets users change lots of things like how information is stored and processed. |
Keywords
» Artificial intelligence » Quantization
