Degree Granting Department
Computer Science and Engineering
Nagarajan Ranganathan, Ph.D
Srinivas Katkoori, Ph.D.
Hao Zheng, Ph.D.
Michael Weng, Ph.D.
Brendan Nagle, Ph.D.
Soft Errors, Power, Variations, Architecture, Clustering
Reliability is an important issue in very large scale integration(VLSI) circuits. In the absence of a focus on reliability in the design process, a circuit’s functionality can be compromised. Since chips are fabricated in bulk, if reliability issues are diagnosed during the manufacturing of the design, the faulty chips must be tossed, which reduces product yield and increases cost. Being aware of this situation, chip designers attempt to resolve as many issues dealing with reliability on the front-end of the design phase (architecture or systemlevel modeling) to minimize the cost of errors in the design which increases as the design phase matures. Chip designers have been known to allocate a large amount of resources to reliability of a chip to maintain confidence in their product as well as to reduce the cost due to errors found in the design. The reliability of a design is often degraded by various causes ranging from soft errors, electro-migration, hot carrier injection, negative bias temperature instability (NBTI), crosstalk, power supply noise and variations in the physical design. Given the continuing scaling down of circuit designs achievable by the advancement in technology, the issues pertaining to reliability have a greater impact within the design.
Given this problem along with the demand for high-performance designs, chip designers are faced with objective to design reliable circuits, that are high performance and energyefficient. This is especially important given the huge growth in mobile battery-operated electronic devices in the market. In prior research, there has been significant contributions to increasing the reliability of VLSI designs, however such techniques are often computationally expensive or power intensive.
In this dissertation, we develop a set of new techniques to generate reliable designs by minimizing soft error, peak power and variation effects. Several techniques at the architectural level to detect soft errors with minimal performance overhead, that make use of data, information, temporal and spatial redundancy are proposed. The techniques are designed in such a way that much of their latency overhead can be hidden by the latency of other functional operations. It is shown that the proposed methodologies can be implemented with negligible or minimal performance overhead hidden by critical path operations in the datapath. In designs with large peak power values, high current spikes cause noise within the power supply creating timing issues in the circuit which affect its functionality. A path clustering algorithm is proposed which attempts to normalize the current draw in the circuit over the circuit’s clock period by delaying the start times of certain paths. By reducing the number of paths starting at a time instance, we reduce the amount of current drawn from the power supply is reduced. Experimental results indicate a reduction of up to 72% in peak power values when tested on the ISCAS ’85 and OpenCores benchmarks. Variations in VLSI designs come from process, voltage supply, and Temperature (PVT). These variations in the design cause non-ideal behavior at random internal nodes which impacts the timing of the design. A variation aware circuit level design methodology is presented in this dissertation in which the architecture dynamically stretches the clock when the effect of an variation effects are observed within the circuit during computations. While previous research efforts found are directed towards reducing variation effects, this technique offers an alternative approach to adapt dynamically to variation effects. The design technique is shown to increase in timing yield on ITC ’99 benchmark circuits by an average of 41% with negligible area overhead.
Scholar Commons Citation
Hyman Jr, Ransford Morel, "Techniques for Enhancing Reliability in VLSI Circuits" (2011). USF Tampa Graduate Theses and Dissertations.