CIDPro: Custom Instructions for Dynamic Program Diversification

Timing side-channel attacks pose a major threat to embedded systems due to their ease of accessibility. We propose CIDPro, a framework that relies on dynamic program diversification to mitigate timing side-channel leakage. The proposed framework integrates the widely used LLVM compiler infrastructure and the increasingly popular RISC-V FPGA soft-processor. The compiler automatically generates custom instructions in the security critical segments of the program, and the instructions execute on the RISC-V custom co-processor to produce diversified timing characteristics on each execution instance. CIDPro has been implemented on the Zynq7000 XC7Z020 FPGA device to study the performance overhead and security tradeoffs. Experimental results show that our solution can achieve 80% and 86% timing side-channel capacity reduction for two benchmarks with an acceptable performance overhead compared to existing solutions. In addition, the proposed method incurs only a negligible hardware area overhead of 1% slices of the entire RISC-V system

Enabling virtual radio functions on software defined radio for future wireless networks

Today's wired networks have become highly flexible, thanks to the fact that an increasing number of functionalities are realized by software rather than dedicated hardware. This trend is still in its early stages for wireless networks, but it has the potential to improve the network's flexibility and resource utilization regarding both the abundant computational resources and the scarce radio spectrum resources. In this work we provide an overview of the enabling technologies for network reconfiguration, such as Network Function Virtualization, Software Defined Networking, and Software Defined Radio. We review frequently used terminology such as softwarization, virtualization, and orchestration, and how these concepts apply to wireless networks. We introduce the concept of Virtual Radio Function, and illustrate how softwarized/virtualized radio functions can be placed and initialized at runtime, allowing radio access technologies and spectrum allocation schemes to be formed dynamically. Finally we focus on embedded Software-Defined Radio as an end device, and illustrate how to realize the placement, initialization and configuration of virtual radio functions on such kind of devices

NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps

Convolutional neural networks (CNNs) have become the dominant neural network architecture for solving many state-of-the-art (SOA) visual processing tasks. Even though Graphical Processing Units (GPUs) are most often used in training and deploying CNNs, their power efficiency is less than 10 GOp/s/W for single-frame runtime inference. We propose a flexible and efficient CNN accelerator architecture called NullHop that implements SOA CNNs useful for low-power and low-latency application scenarios. NullHop exploits the sparsity of neuron activations in CNNs to accelerate the computation and reduce memory requirements. The flexible architecture allows high utilization of available computing resources across kernel sizes ranging from 1x1 to 7x7. NullHop can process up to 128 input and 128 output feature maps per layer in a single pass. We implemented the proposed architecture on a Xilinx Zynq FPGA platform and present results showing how our implementation reduces external memory transfers and compute time in five different CNNs ranging from small ones up to the widely known large VGG16 and VGG19 CNNs. Post-synthesis simulations using Mentor Modelsim in a 28nm process with a clock frequency of 500 MHz show that the VGG19 network achieves over 450 GOp/s. By exploiting sparsity, NullHop achieves an efficiency of 368%, maintains over 98% utilization of the MAC units, and achieves a power efficiency of over 3TOp/s/W in a core area of 6.3mm$^2$. As further proof of NullHop's usability, we interfaced its FPGA implementation with a neuromorphic event camera for real time interactive demonstrations

A CAD Tool for Synthesizing Optimized Variants of Altera\u27s Nios II Soft-Core Processor

Soft-core processors offer embedded system designers the benefits of customization, flexibility and reusability. Altera\u27s NIOS II soft-core processor is a popular, commercially available soft-core processor that can be implemented on a variety of Altera FPGAs. In this thesis, the Nios II soft-core processor from Altera Corporation was studied and a VHDL implementation, called UW_Nios II, was developed. UW_Nios II was developed to enable us to perform design space exploration (DSE) for the Nios II processor. It was evaluated and compared with Altera Nios II and shown to be competitive. SCBuild is an existing CAD tool that was developed to enable DSE of soft-core processors. We modified SCBuild to automatically explore the design space of the UW_Nios II using a genetic algorithm. This tool can accurately estimate the area and critical path delay of different variants of the UW_Nios II on a field programmable gate array. Through experiments conducted using SCBuild, it was shown that employing a genetic algorithm to explore the design space of parameterized Nios II core, with a large design space, helps designers find optimized variants of UW_Nios II

A Framework for the Design and Analysis of High-Performance Applications on FPGAs using Partial Reconfiguration

The field-programmable gate array (FPGA) is a dynamically reconfigurable digital logic chip used to implement custom hardware. The large densities of modern FPGAs and the capability of the on-thely reconfiguration has made the FPGA a viable alternative to fixed logic hardware chips such as the ASIC. In high-performance computing, FPGAs are used as co-processors to speed up computationally intensive processes or as autonomous systems that realize a complete hardware application. However, due to the limited capacity of FPGA logic resources, denser FPGAs must be purchased if more logic resources are required to realize all the functions of a complex application. Alternatively, partial reconfiguration (PR) can be used to swap, on demand, idle components of the application with active components. This research uses PR to swap components to improve the performance of the application given the limited logic resources available with smaller but economical FPGAs. The swap is called ”resource sharing PR”. In a pipelined design of multiple hardware modules (pipeline stages), resource sharing PR is a technique that uses PR to improve the performance of pipeline bottlenecks. This is done by reconfiguring other pipeline stages, typically those that are idle waiting for data from a bottleneck, into an additional parallel bottleneck module. The target pipeline of this research is a two-stage “slow-toast” pipeline where the flow of data traversing the pipeline transitions from a relatively slow, bottleneck stage to a fast stage. A two stage pipeline that combines FPGA-based hardware implementations of well-known Bioinformatics search algorithms, the X! Tandem algorithm and the Smith-Waterman algorithm, is implemented for this research; the implemented pipeline demonstrates that characteristics of these algorithm. The experimental results show that, in a database of unknown peptide spectra, when matching spectra with 388 peaks or greater, performing resource sharing PR to instantiate a parallel X! Tandem module is worth the cost for PR. In addition, from timings gathered during experiments, a general formula was derived for determining the value of performing PR upon a fast module

Method for dynamic power monitoring on FPGAs

International audienceThe ever-increasing integration densities make it possible to configure multi-core systems composed of hundreds of blocks on existing FPGAs that may influence overall consumption differently. Observing total consumption is not sufficient to accurately assess internal circuit activity to be able to deploy effective adaptation strategies. In this case monitoring techniques are required. This paper presents a CAD flow for high-level dynamic power estimation on FPGAs. The method is based on the monitoring of toggling activity for relevant signals by introducing event counters. The appropriate signals are selected using the Greedy Stepwise filter. Our approach is based on a generic method that is able to produce a power model for any block-based circuit. We evaluated our contribution on a SoC RTL model implemented on Spartan3, Virtex5, and Spartan6 FPGAs. A power model and monitors are automatically generated to achieve the best tradeoff between accuracy and overhead