Date: Tuesday 25 March 2014
Time: 17:00 - 18:30
Location / Room: Konferenz 2

Chair:
Ian O'Connor, University of Lyon, FR

Co-Chair:
Michael Niemier, University of Notre Dame, US

The three papers in this session all address "nearer-term" emerging technologies. Stochastic computing techniques are becoming increasingly relevant as CMOS becomes more error prone, numerous industrial and academic efforts are targeting 3D integration, and integrated microfluidics promise to have a profound impact on healthcare and other domains.

Time	Label	Presentation Title Authors
17:00	4.4.1	IIR FILTERS USING STOCHASTIC ARITHMETIC Speakers: Naman Saraf, Kia Bazargan, David J Lilja and Marc D Riedel, University of Minnesota, Twin Cities, US Abstract We consider the design of IIR filters operating on oversampled sigma-delta modulated bit streams using stochastic arithmetic. Conventional digital filters process multi-bit data at the Nyquist rate using multi-bit multipliers and adders. High resolution ADCs based on the sigma-delta modulation generate random bits at an oversampled rate as intermediate data. We propose to filter the sigma-delta modulated bit streams directly and present first and second order low pass IIR filters based on the stochastic integrator. Experimental results show a significant reduction in hardware area by using stochastic filters.
17:30	4.4.2	EFFICIENT TRANSIENT THERMAL SIMULATION OF 3D ICS WITH LIQUID-COOLING AND THROUGH SILICON VIAS Speakers: Alain Fourmigue, Giovanni Beltrame and Gabriela Nicolescu, Polytechnique Montreal, CA Abstract Three-dimensional integrated circuits (3D ICs) with advanced cooling systems are emerging as a viable solution for many-core platforms. These architectures generate a high and rapidly changing thermal flux. Their design requires accurate transient thermal models. Several models have been proposed, either with limited capabilities, or poor simulation performance. This work introduces an efficient algorithm based on the Finite Difference Method to compute the transient temperature in 3D ICs. Our experiments show a 5x speedup versus state-of-the-art models, while maintaining the same level of accuracy, and demonstrate the effect of large through silicon vias arrays on thermal dissipation.
18:00	4.4.3	A LOGIC INTEGRATED OPTIMAL PIN-COUNT DESIGN FOR DIGITAL MICROFLUIDIC BIOCHIPS Speakers: Trung Anh Dinh1, Shigeru Yamashita1 and Tsung-Yi Ho2 1Ritsumeikan University, JP; 2National Cheng Kung University, TW Abstract Digital microfluidic biochips have become one of the most promising technologies for biomedical experiments. In modern microfluidic technology, reducing the number of independent control pins that reflects most of the fabrication cost, power consumption and reliability of a microfluidic system, is a key challenge for every digital microfluidic biochip design. However, all the previous chip designs sacrifice the optimality of the problem, and only limited reduction on the number of control pins is observed. Moreover, most existing designs cannot satisfy high-throughput demand for bioassays, and thus inapplicable in practical contexts. In this paper, we propose the first optimal pin-count design scheme for digital microfluidic biochips. By integrating a very simple combinational logic circuit into the original chip, the proposed scheme can provide high-throughput for bioassays with an information-theoretic minimum number of control pins. Furthermore, to cope with the rapid growth of the chip's scale, we also propose a scalable and efficient heuristics. Experiments demonstrate that the proposed scheme can obtain much fewer number of control pins compared with the previous state-of-the-art works.
18:30	IP2-1, 978	FAST AND ACCURATE COMPUTATION USING STOCHASTIC CIRCUITS Speakers: Armin Alaghi and John P. Hayes, University of Michigan - Ann Arbor, US Abstract Stochastic computing (SC) is a low-cost design technique that has great promise in applications such as image processing. SC enables arithmetic operations to be performed on stochastic bit-streams using ultra-small and low-power circuitry. However, accurate computations tend to require long run-times due to the random fluctuations inherent in stochastic numbers (SNs). We present novel techniques for SN generation that lead to better accuracy/run-time trade-offs. First, we analyze a property called progressive precision (PP) which allows computational accuracy to grow systematically with run-time. Second, borrowing from Monte Carlo methods, we show that SC performance can be greatly improved by replacing the usual pseudo-random number sources by low-discrepancy (LD) sequences that are predictably progressive. Finally, we evaluate the use of LD stochastic numbers in SC, and show they can produce significantly faster and more accurate results than existing stochastic designs.
18:30		End of session Exhibition Reception in Several serving points inside the Exhibition Area (Terrace Level) The Exhibition Reception will take place in the exhibition area (Terrace Level). All exhibitors are welcome to provide drinks and snacks for delegates and visitors.