Person:

Lyons, Michael John

Recording large data sets in current wireless sensor networks is difficult if not impossible, as sensor network nodes feature extremely limited capabilities. Meager amounts of memory limit storage and slow network transmission rates limit data transfer. Even if enough data is recorded, network lifetime may be brief due to energy consumption. In this paper, we discuss using Bloom filters to reduce the memory and network transmission requirements for sending or storing large amounts of data. Using our approach, we can gather more information from our wireless sensor network and simultaneously extend the network lifetime.

In recent years, circuit reliability in modern high-performance processors has become increasingly important. Shrinking feature sizes and diminishing supply voltages have made circuits more sensitive to microprocessor supply voltage fluctuations. These fluctuations result from the natural variation of processor activity as workloads execute, but when left unattended, these voltage fluctuations can lead to timing violations or even transistor lifetime issues. In this article, we present a hardware--software collaborative approach to mitigate voltage fluctuations. A checkpoint-recovery mechanism rectifies errors when voltage violates maximum tolerance settings, while a runtime software layer reschedules the program's instruction stream to prevent recurring violations at the same program location. The runtime layer, combined with the proposed code-rescheduling algorithm, removes 60% of all violations with minimal overhead, thereby significantly improving overall performance. Our solution is a radical departure from the ongoing industry-standard approach to circumvent the issue altogether by optimizing for the worst-case voltage flux, which compromises power and performance efficiency severely, especially looking ahead to future technology generations. Existing conservative approaches will have severe implications on the ability to deliver efficient microprocessors. The proposed technique reassembles a traditional reliability problem as a runtime performance optimization problem, thus allowing us to design processors for typical case operation by building intelligent algorithms that can prevent recurring violations.

RTL design complexity discouraged adoption of reconfigurable logic in general purpose systems, impeding opportunities for performance and energy improvements. Recent improvements to HLS compilers simplify RTL design and are easing this barrier. A new challenge will emerge: managing reconfigurable resources between multiple applications with custom hardware designs. In this paper, we propose a method to "shrink-fit" accelerators within widely varying fabric budgets. Shrink-fit automatically shrinks existing accelerator designs within small fabric budgets and grows designs to increase performance when larger budgets are available. Our method takes advantage of current accelerator design techniques and introduces a novel architectural approach based on fine-grained virtualization. We evaluate shrink-fit using a synthesized implementation of an IDCT for decoding JPEGs and show the IDCT accelerator can shrink by a factor of 16x with minimal performance and area overheads. Using shrink-fit, application designers can achieve the benefits of hardware acceleration with single RTL designs on FPGAs large and small.

Hardware accelerators provide a rare opportunity to achieve orders-of-magnitude performance and power improvements with customized circuit designs.