What is Software Defined Architecture (SODA) in the context of machine learning and hardware synthesis?

Answered on : 2024-01-24

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End-to-End Synthesis of Dynamically Controlled Machine ...

ieeexplore.ieee.org

SODA: An End-To-End Open-Source Hardware Compiler ...

fastpathconference.github.io

Software Defined FPGA based Accelerators for Big Data

date-conference.com

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Software Defined Architecture (SODA) is a framework used in the context of machine learning and hardware synthesis. It involves the synthesis of dynamically controlled machine learning models for acceleration. The SODA framework is built upon the multilevel intermediate representation (MLIR) framework. Here's a brief overview of SODA's role in machine learning and hardware synthesis:

1. **ML Model Integration:** SODA ingests pre-trained machine learning models.

2. **Kernel Identification:** It identifies specific kernels or components of these models suitable for hardware acceleration.

3. **High-Level Optimizations:** SODA performs high-level optimizations on these kernels.

4. **Hardware Synthesis:** Finally, it prepares these optimized components for hardware synthesis, making them suitable for efficient execution on hardware accelerators.

SODA is an open-source framework that enhances the performance of machine learning models by optimizing and accelerating their execution on hardware platforms, contributing to faster and more efficient machine learning tasks in various applications [1][4].