Test-Delivery Optimization in Manycore SOCs

We present two test-data delivery optimization algorithms for system-on-chip (SOC) designs with hundreds of cores, where a network-on-chip (NOC) is used as the interconnection fabric. We first present an e ective algorithm based on a subsetsum formulation to solve the test-delivery problem in NOCs with arbitrary topology that use dedicated routing. We further propose an algorithm for the important class of NOCs with grid topology and XY routing. The proposed algorithm is the first to co-optimize the number of access points, access-point locations, pin distribution to access points, and assignment of cores to access points for optimal test resource utilization of such NOCs. Testtime minimization is modeled as an NOC partitioning problem and solved with dynamic programming in polynomial time. Both the proposed methods yield high-quality results and are scalable to large SOCs with many cores. We present results on synthetic grid topology NOC-based SOCs constructed using cores from the ITC’02 benchmark, and demonstrate the scalability of our approach for two SOCs of the future, one with nearly 1,000 cores and the other with 1,600 cores. Test scheduling under power constraints is also incorporated in the optimization framework

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

Test Planning and Test Access Mechanism Design for 3D SICs

In this paper we propose a scheme for test planning and test access mechanism (TAM) design for stacked integrated circuits (SICs) that are designed in a core-based manner. Our scheme minimizes the test cost, which is given as the weighted sum of the test time and the TAM width. The test cost is evaluated for a test flow that consists of a wafer sort test of each individual chip and a package test of the complete stack of chips. We use an Integer Linear Programming (ILP) model to find the optimal test cost. The ILP model is implemented on several designs constructed from ITC’02 benchmarks. The experimental results show significant reduction in test cost compared to when using schemes, which are optimized for non-stacked chips

Test Planning for 3D SICs using ILP

In this paper we propose a test planning scheme for corebased 3D stacked integrated circuits where the total test cost for wafer sort of each individual chip and the test cost of the complete stack at package test is minimized. We use an Integer Linear Programming (ILP) model to find the optimal test cost, which is given as the weighted sum of the test time and the test access mechanism (TAM). As ILP is time consuming, we use a scheme to bound the test time and the TAM such that the search space is reduced. The proposed bounding scheme and the ILP model were applied on several ITC’02 benchmarks and the results show that optimal solutions were obtained at low computation time

A Survey of Prediction and Classification Techniques in Multicore Processor Systems

In multicore processor systems, being able to accurately predict the future provides new optimization opportunities, which otherwise could not be exploited. For example, an oracle able to predict a certain application\u27s behavior running on a smart phone could direct the power manager to switch to appropriate dynamic voltage and frequency scaling modes that would guarantee minimum levels of desired performance while saving energy consumption and thereby prolonging battery life. Using predictions enables systems to become proactive rather than continue to operate in a reactive manner. This prediction-based proactive approach has become increasingly popular in the design and optimization of integrated circuits and of multicore processor systems. Prediction transforms from simple forecasting to sophisticated machine learning based prediction and classification that learns from existing data, employs data mining, and predicts future behavior. This can be exploited by novel optimization techniques that can span across all layers of the computing stack. In this survey paper, we present a discussion of the most popular techniques on prediction and classification in the general context of computing systems with emphasis on multicore processors. The paper is far from comprehensive, but, it will help the reader interested in employing prediction in optimization of multicore processor systems