Invited Paper: FEMU: An Open-Source and Configurable Emulation Framework for Prototyping TinyAI Heterogeneous Systems

TL;DR

This paper introduces FEMU, an open-source, configurable FPGA-based emulation framework designed for rapid prototyping and evaluation of TinyAI heterogeneous systems, combining hardware reconfigurability with software control.

Contribution

The paper presents FEMU, a novel FPGA emulation framework that integrates hardware and software components for efficient prototyping of TinyAI systems, demonstrated through the X-HEEP-FEMU platform.

Findings

Successfully deployed on Xilinx Zynq-7020 FPGA

Integrates hardware energy models with software environment

Enables rapid prototyping of TinyAI heterogeneous systems

Abstract

In this paper, we present the new FPGA EMUlation (FEMU), an open-source and configurable emulation framework for prototyping and evaluating TinyAI heterogeneous systems (HS). FEMU leverages the capability of system-on-chip (SoC)-based FPGAs to combine the under-development HS implemented in a reconfigurable hardware region (RH) for quick prototyping with a software environment running under a standard operating system in a control software region (CS) for supervision and communication. To evaluate our approach, we built the X-HEEP FPGA EMUlation (X-HEEP-FEMU) platform by instantiating the proposed framework with real-world hardware and software components. X-HEEP-FEMU is deployed on the Xilinx Zynq-7020 SoC and integrates the eXtendible Heterogeneous Energy Efficient Platform (X-HEEP) host in the RH, a Linux-based Python environment on the ARM Cortex-A9 CS, and energy models derived from a TSMC 65 nm CMOS silicon implementation of X-HEEP, called HEEPocrates.