VLSI Implementation of Deep Neural Network Using Integral Stochastic Computing

The hardware implementation of deep neural networks (DNNs) has recently received tremendous attention: many applications in fact require high-speed operations that suit a hardware implementation. However, numerous elements and complex interconnections are usually required, leading to a large area occupation and copious power consumption. Stochastic computing has shown promising results for low-power area-efficient hardware implementations, even though existing stochastic algorithms require long streams that cause long latencies. In this paper, we propose an integer form of stochastic computation and introduce some elementary circuits. We then propose an efficient implementation of a DNN based on integral stochastic computing. The proposed architecture has been implemented on a Virtex7 FPGA, resulting in 45% and 62% average reductions in area and latency compared to the best reported architecture in literature. We also synthesize the circuits in a 65 nm CMOS technology and we show that the proposed integral stochastic architecture results in up to 21% reduction in energy consumption compared to the binary radix implementation at the same misclassification rate. Due to fault-tolerant nature of stochastic architectures, we also consider a quasi-synchronous implementation which yields 33% reduction in energy consumption w.r.t. the binary radix implementation without any compromise on performance.Comment: 11 pages, 12 figure

DeSyRe: on-Demand System Reliability

The DeSyRe project builds on-demand adaptive and reliable Systems-on-Chips (SoCs). As fabrication technology scales down, chips are becoming less reliable, thereby incurring increased power and performance costs for fault tolerance. To make matters worse, power density is becoming a significant limiting factor in SoC design, in general. In the face of such changes in the technological landscape, current solutions for fault tolerance are expected to introduce excessive overheads in future systems. Moreover, attempting to design and manufacture a totally defect and fault-free system, would impact heavily, even prohibitively, the design, manufacturing, and testing costs, as well as the system performance and power consumption. In this context, DeSyRe delivers a new generation of systems that are reliable by design at well-balanced power, performance, and design costs. In our attempt to reduce the overheads of fault-tolerance, only a small fraction of the chip is built to be fault-free. This fault-free part is then employed to manage the remaining fault-prone resources of the SoC. The DeSyRe framework is applied to two medical systems with high safety requirements (measured using the IEC 61508 functional safety standard) and tight power and performance constraints

A FPGA-Based Reconfigurable Software Architecture for Highly Dependable Systems

Nowadays, systems-on-chip are commonly equipped with reconfigurable hardware. The use of hybrid architectures based on a mixture of general purpose processors and reconfigurable components has gained importance across the scientific community allowing a significant improvement of computational performance. Along with the demand for performance, the great sensitivity of reconfigurable hardware devices to physical defects lead to the request of highly dependable and fault tolerant systems. This paper proposes an FPGA-based reconfigurable software architecture able to abstract the underlying hardware platform giving an homogeneous view of it. The abstraction mechanism is used to implement fault tolerance mechanisms with a minimum impact on the system performanc

Avionics architecture studies for the entry research vehicle

This report is the culmination of a year-long investigation of the avionics architecture for NASA's Entry Research Vehicle (ERV). The Entry Research Vehicle is conceived to be an unmanned, autonomous spacecraft to be deployed from the Shuttle. It will perform various aerodynamic and propulsive maneuvers in orbit and land at Edwards AFB after a 5 to 10 hour mission. The design and analysis of the vehicle's avionics architecture are detailed here. The architecture consists of a central triply redundant ultra-reliable fault tolerant processor attached to three replicated and distributed MIL-STD-1553 buses for input and output. The reliability analysis is detailed here. The architecture was found to be sufficiently reliable for the ERV mission plan

Investigation into the wafer-scale integration of fine-grain parallel processing computer systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This thesis investigates the potential of wafer-scale integration (WSI) for the implementation of low-cost fine-grain parallel processing computer systems. As WSI is a relatively new subject, there was little work on which to base investigations. Indeed, most WSI architectures existed only as untried and sometimes vague proposals. Accordingly, the research strategy approached this problem by identifying a representative WSI structure and architecture on which to base investigations. An analysis of architectural proposals identified associative memory to be general purpose parallel processing component used in a wide range of WSI architectures. Furthermore, this analysis provided a set of WSI-level design requirements to evaluate the sustainability of different architectures as research vehicles. The WSI-ASP (WASP) device, which has a large associative memory as its main component is shown to meet these requirements and hence was chosen as the research vehicle. Consequently, this thesis addresses WSI potential through an in-depth investigation into the feasibility of implementing a large associative memory for the WASP device that meets the demanding technological constraints of WSI. Overall, the thesis concludes that WSI offers significant potential for the implementation of low-cost fine-grain parallel processing computer systems. However, due to the dual constraints of thermal management and the area required for the power distribution network, power density is a major design constraint in WSI. Indeed, it is shown that WSI power densities need to be an order of magnitude lower than VLSI power densities. The thesis demonstrates that for associative memories at least, VLSI designs are unsuited to implementation in WSI. Rather, it is shown that WSI circuits must be closely matched to the operational environment to assure suitable power densities. These circuits are significantly larger than their VLSI equivalents. Nonetheless, the thesis demonstrates that by concentrating on the most power intensive circuits, it is possible to achieve acceptable power densities with only a modest increase in area overheads.SER