Clinton W. Kelly

An ultra low-power processor for sensor networks

We present a novel processor architecture designed specifically for use in low-power wireless sensor-network nodes. Our sensor network asynchronous processor (SNAP/LE) is based on an asynchronous data-driven 16-bit RISC core with an extremely low-power idle state, and a wakeup response latency on the order of tens of nanoseconds. The processor instruction set is optimized for sensor-network applications, with support for event scheduling, pseudo-random number generation, bitfield operations, and radio/sensor interfaces. SNAP/LE has a hardware event queue and event coprocessors, which allow the processor to avoid the overhead of operating system software (such as task schedulers and external interrupt servicing), while still providing a straightforward programming interface to the designer. The processor can meet performance levels required for data monitoring applications while executing instructions with tens of picojoules of energy.We evaluate the energy consumption of SNAP/LE with several applications representative of the workload found in data-gathering wireless sensor networks. We compare our architecture and software against existing platforms for sensor networks, quantifying both the software and hardware benefits of our approach.

SNAP: a Sensor-Network Asynchronous Processor

We present a Sensor-Network Asynchronous Processor (SNAP), which we have designed to be both a processor core for a sensor-network node and a component of a chip multiprocessor, the Network on a Chip (NoC), which will execute a novel sensor-network simulator. We discuss the advantages of using the same processor for nodes in physical and simulated sensor networks. We describe the attributes that a processor must possess to function well in both roles, and we then describe the way we designed SNAP to have these attributes.

BitSNAP: dynamic significance compression for a low-energy sensor network asynchronous processor

We present a novel asynchronous processor architecture called BitSNAP that utilizes bit-serial datapaths with dynamic significance compression to yield extremely low-energy consumption. Based on the sensor network asynchronous processor (SNAP) ISA, BitSNAP can reduce datapath energy consumption by 50% over a comparable parallel-word processor, while still providing performance suited for powering low-energy sensor network nodes. In 180 nm CMOS, the processor is expected to run at between 6 and 54 MIPS while consuming 152 pJ/ins at 1.8 V and just 17 pJ/ins at 0.6 V.

An event-synchronization protocol for parallel simulation of large-scale wireless networks

We present a new conservative event-synchronization protocol, a time-based synchronization, for parallel discrete-event simulation of mobile ad hoc wireless networks. Simulators that use our protocol proceed at a scaled version of real time and send messages that correspond only to transmissions in the simulated network. We show that such simulators can maintain a constant execution time even as the sizes of the networks that they simulate grow. Moreover, we show that these simulators, when executed on a custom parallel architecture, are capable of simulating many networks faster than real time.

Network on a chip: modeling wireless networks with asynchronous VLSI

We introduce the notion of a network on a chip: a programmable asynchronous VLSI architecture for fast and efficient simulation of wireless networks. The approach is inspired by the remarkable similarity between networks and asynchronous VLSI. Our approach results in simulators that can evaluate network scenarios much faster than real time, enabling a new class of network protocols that can dynamically change their behavior based on feedback from in situ simulation. We describe our simulation architecture, and present results that validate our approach.

A radiation hardened reconfigurable FPGA

A new high density, high performance radiation hardened, reconfigurable Field Programmable Gate Array (FPGA) is being developed by Achronix Semiconductor and BAE Systems for use in space and other radiation hardened applications. The reconfigurable FPGA fabric architecture utilizes Achronix Semiconductor novel picoPIPE technology and it is being manufactured at BAE Systems using their strategically radiation hardened 150 nm epitaxial bulk CMOS technology, called RH15. Circuits built in RH15 consistently demonstrate megarad total dose hardness and the picoPIPE asynchronous technology has been adapted for use in space with a Redundancy Voting Circuit (RVC) methodology to protect the user circuits from single event effects.

Mitigation of single-event charge sharing in a commercial FPGA architecture

The motivation for single event effects (SEE) analysis and mitigation as part of the process for adaptation of a commercial Field Programmable Gate Array (FPGA) architecture for space-qualified applications is discussed. The interdependent roles of heavy-ion and laser-induced upset evaluation coupled with computer-aided investigations of SEE mechanisms and mitigation techniques in this process are shown to enable a significant reduction in SEE sensitivity of the device, while achieving minimal impact on remanufacturing steps.