Weighted p-bits for FPGA implementation of probabilistic circuits

Probabilistic spin logic (PSL) is a recently proposed computing paradigm based on unstable stochastic units called probabilistic bits (p-bits) that can be correlated to form probabilistic circuits (p-circuits). These p-circuits can be used to solve problems of optimization, inference and also to implement precise Boolean functions in an "inverted" mode, where a given Boolean circuit can operate in reverse to find the input combinations that are consistent with a given output. In this paper we present a scalable FPGA implementation of such invertible p-circuits. We implement a "weighted" p-bit that combines stochastic units with localized memory structures. We also present a generalized tile of weighted p-bits to which a large class of problems beyond invertible Boolean logic can be mapped, and how invertibility can be applied to interesting problems such as the NP-complete Subset Sum Problem by solving a small instance of this problem in hardware

Normalizing or not normalizing? An open question for floating-point arithmetic in embedded systems

Emerging embedded applications lack of a specific standard when they require floating-point arithmetic. In this situation they use the IEEE-754 standard or ad hoc variations of it. However, this standard was not designed for this purpose. This paper aims to open a debate to define a new extension of the standard to cover embedded applications. In this work, we only focus on the impact of not performing normalization. We show how eliminating the condition of normalized numbers, implementation costs can be dramatically reduced, at the expense of a moderate loss of accuracy. Several architectures to implement addition and multiplication for non-normalized numbers are proposed and analyzed. We show that a combined architecture (adder-multiplier) can halve the area and power consumption of its counterpart IEEE-754 architecture. This saving comes at the cost of reducing an average of about 10 dBs the Signal-to-Noise Ratio for the tested algorithms. We think these results should encourage researchers to perform further investigation in this issue.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

High throughput spatial convolution filters on FPGAs

Digital signal processing (DSP) on field- programmable gate arrays (FPGAs) has long been appealing because of the inherent parallelism in these computations that can be easily exploited to accelerate such algorithms. FPGAs have evolved significantly to further enhance the mapping of these algorithms, included additional hard blocks, such as the DSP blocks found in modern FPGAs. Although these DSP blocks can offer more efficient mapping of DSP computations, they are primarily designed for 1-D filter structures. We present a study on spatial convolutional filter implementations on FPGAs, optimizing around the structure of the DSP blocks to offer high throughput while maintaining the coefficient flexibility that other published architectures usually sacrifice. We show that it is possible to implement large filters for large 4K resolution image frames at frame rates of 30–60 FPS, while maintaining functional flexibility

Multi-operand Decimal Adder Trees for FPGAs

The research and development of hardware designs for decimal arithmetic is currently going under an intense activity. For most part, the methods proposed to implement fixed and floating point operations are intended for ASIC designs. Thus, a direct mapping or adaptation of these techniques into a FPGA could be far from an optimal solution. Only a few studies have considered new methods more suitable for FPGA implementations. A basic operation that has not received enough attention in this context is multi-operand BCD addition. For example, it is of interest for low latency implementations of decimal fixed and floating point multipliers and decimal fused multiply-add units. We have explored the most representative proposals for multi-operand BCD addition and found that the resultant implementations in FPGAs are still very inefficient in terms of both area and latency when compared to their binary counterparts. In this paper we present a new method for fast and efficient implementation of multi-operand BCD addition in current FPGA devices. In particular, our proposal maps quite well into the slice structure of the Xilinx Virtex-5/Virtex-6 families and it is highly pipelineable. The synthesis results for a Virtex-6 device indicate that our implementations halve the area and latency of previous proposals, presenting area and delay figures close to those of optimal binary adder trees.La recherche sur l'implantation en matériel de l'arithmétique décimale est actuellement très active, la plupart des travaux portant sur des opérateurs pour les processeurs, en virgule fixe ou flottante. Mais les techniques développées pour un circuit intégré n'aboutissent pas forcément à une implémentation optimale dans un FPGA. Il n'y a que peu d'études ciblant explicitement les FPGA. Cet article s'intéresse dans ce contexte, à l'addition BCD multi-opérande, au cœur de multiplieurs et de multiplieurs-accumulateurs à faible latence. Nous étudions les architectures proposées pour cette opération décimale, et nous observons que, sur FPGA, leur performance (surface et latence) est très inférieure à celle des opérations binaire à précision comparable. Nous présentons donc dans cet article une nouvelle technique d'addition BCD multi-opérandes qui s'avère plus efficace que les propositions précédentes sur les FPGA actuels. Elle s'adapte particulièrement bien à la structure fine des FPGA Xilinx Virtex-5/Virtex-6, et se prête bien au pipeline. Les résultats de synthèse montrent que notre implémentation divise par deux la surface et la latence par rapport aux propositions précédentes, les ramenant à des valeurs comparables à celles des meilleurs additionneurs multi-opérandes binaires

Hardware Implementation of the GPS authentication

In this paper, we explore new area/throughput trade- offs for the Girault, Poupard and Stern authentication protocol (GPS). This authentication protocol was selected in the NESSIE competition and is even part of the standard ISO/IEC 9798. The originality of our work comes from the fact that we exploit a fixed key to increase the throughput. It leads us to implement GPS using the Chapman constant multiplier. This parallel implementation is 40 times faster but 10 times bigger than the reference serial one. We propose to serialize this multiplier to reduce its area at the cost of lower throughput. Our hybrid Chapman's multiplier is 8 times faster but only twice bigger than the reference. Results presented here allow designers to adapt the performance of GPS authentication to their hardware resources. The complete GPS prover side is also integrated in the network stack of the PowWow sensor which contains an Actel IGLOO AGL250 FPGA as a proof of concept.Comment: ReConFig - International Conference on ReConFigurable Computing and FPGAs (2012

Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions

In the past decade, Convolutional Neural Networks (CNNs) have demonstrated state-of-the-art performance in various Artificial Intelligence tasks. To accelerate the experimentation and development of CNNs, several software frameworks have been released, primarily targeting power-hungry CPUs and GPUs. In this context, reconfigurable hardware in the form of FPGAs constitutes a potential alternative platform that can be integrated in the existing deep learning ecosystem to provide a tunable balance between performance, power consumption and programmability. In this paper, a survey of the existing CNN-to-FPGA toolflows is presented, comprising a comparative study of their key characteristics which include the supported applications, architectural choices, design space exploration methods and achieved performance. Moreover, major challenges and objectives introduced by the latest trends in CNN algorithmic research are identified and presented. Finally, a uniform evaluation methodology is proposed, aiming at the comprehensive, complete and in-depth evaluation of CNN-to-FPGA toolflows.Comment: Accepted for publication at the ACM Computing Surveys (CSUR) journal, 201