SW-VHDL Co-Verification Environment Using Open Source Tools

The verification of complex digital designs often involves the use of expensive simulators. The present paper proposes an approach to verify a specific family of complex hardware/software systems, whose hardware part, running on an FPGA, communicates with a software counterpart executed on an external processor, such as a user/operator software running on an external PC. The hardware is described in VHDL and the software may be described in any computer language that can be interpreted or compiled into a (Linux) executable file. The presented approach uses open source tools, avoiding expensive license costs and usage restrictions.Unión Europea 68722

CNN2Gate: an implementation of convolutional neural networks inference on FPGAs with automated design space exploration

ABSTRACT: Convolutional Neural Networks (CNNs) have a major impact on our society, because of the numerous services they provide. These services include, but are not limited to image classification, video analysis, and speech recognition. Recently, the number of researches that utilize FPGAs to implement CNNs are increasing rapidly. This is due to the lower power consumption and easy reconfigurability that are offered by these platforms. Because of the research efforts put into topics, such as architecture, synthesis, and optimization, some new challenges are arising for integrating suitable hardware solutions to high-level machine learning software libraries. This paper introduces an integrated framework (CNN2Gate), which supports compilation of a CNN model for an FPGA target. CNN2Gate is capable of parsing CNN models from several popular high-level machine learning libraries, such as Keras, Pytorch, Caffe2, etc. CNN2Gate extracts computation flow of layers, in addition to weights and biases, and applies a “given” fixed-point quantization. Furthermore, it writes this information in the proper format for the FPGA vendor’s OpenCL synthesis tools that are then used to build and run the project on FPGA. CNN2Gate performs design-space exploration and fits the design on different FPGAs with limited logic resources automatically. This paper reports results of automatic synthesis and design-space exploration of AlexNet and VGG-16 on various Intel FPGA platforms