Exploring Approximate Accelerator Architectures Using FPGA Automation Framework

Time Stamp: March 10, 2023 7:41 PM
Source Node: 2513626

The use of Field Programmable Gate Arrays (FPGAs) to explore approximate accelerator architectures is becoming increasingly popular. FPGAs are a type of integrated circuit that can be programmed to perform specific tasks, making them ideal for exploring new architectures. Additionally, FPGAs are often used in high-performance computing applications, making them an ideal platform for exploring approximate accelerator architectures.

The FPGA Automation Framework (FAF) is a software platform that allows users to quickly and easily explore approximate accelerator architectures using FPGAs. FAF provides a comprehensive set of tools for designing, simulating, and testing approximate accelerators on FPGAs. It also provides a library of pre-defined approximate accelerators that can be used as a starting point for exploration.

Using FAF, users can quickly and easily explore different approximate accelerator architectures. This allows them to quickly identify the best architecture for a particular application. Additionally, FAF provides a powerful set of tools for optimizing the performance of the approximate accelerator. This includes tools for tuning the parameters of the accelerator, such as the number of processing elements, the type of memory accesses, and the dataflow patterns.

FAF also provides a library of pre-defined approximate accelerators that can be used as a starting point for exploration. This library includes accelerators for common tasks such as matrix multiplication, convolution, and sorting. Additionally, FAF provides a powerful set of tools for customizing these accelerators to meet specific application requirements.

Finally, FAF provides a comprehensive set of tools for debugging and validating approximate accelerators. This includes tools for tracing the execution of the accelerator and for verifying the correctness of its output. Additionally, FAF provides tools for analyzing the performance of the accelerator and for identifying potential areas for improvement.

In summary, FPGA Automation Framework is an ideal platform for exploring approximate accelerator architectures. It provides a comprehensive set of tools for designing, simulating, and testing approximate accelerators on FPGAs. Additionally, it provides a library of pre-defined approximate accelerators and powerful tools for customizing these accelerators to meet specific application requirements. Finally, it provides a comprehensive set of tools for debugging and validating approximate accelerators.