AI/ML Algorithms and Applications in VLSI Design and Technology

An evident challenge ahead for the integrated circuit (IC) industry in the nanometer regime is the investigation and development of methods that can reduce the design complexity ensuing from growing process variations and curtail the turnaround time of chip manufacturing. Conventional methodologies employed for such tasks are largely manual; thus, time-consuming and resource-intensive. In contrast, the unique learning strategies of artificial intelligence (AI) provide numerous exciting automated approaches for handling complex and data-intensive tasks in very-large-scale integration (VLSI) design and testing. Employing AI and machine learning (ML) algorithms in VLSI design and manufacturing reduces the time and effort for understanding and processing the data within and across different abstraction levels via automated learning algorithms. It, in turn, improves the IC yield and reduces the manufacturing turnaround time. This paper thoroughly reviews the AI/ML automated approaches introduced in the past towards VLSI design and manufacturing. Moreover, we discuss the scope of AI/ML applications in the future at various abstraction levels to revolutionize the field of VLSI design, aiming for high-speed, highly intelligent, and efficient implementations

Block level voltage

Over the past years, state-of-art power optimization methods move towards higher abstraction levels that result in more efficient power savings. Among existing power optimization approaches, dynamic power management (DPM) is considered to be one of the most effective strategies. Depending on abstraction levels, DPM can be implemented in different formats but here we focus on scheduling that is more suitable for real-time system design use. This differs from the concurrent scheduling approaches that start from either the HLS (High-Level Synthesis) or RTS (Real-Time System) point of view, we propose a synergy solution of both approaches, namely block-level voltage/frequency scheduling (BLVFS). The presented block-level voltage/ frequency scheduling approach shows a generic solution for low power SoC (System on Chip) system design while the approaches which belong to the HLS and RTS categories have a strong dependency on the system functionalities. Consider a SoC as a combination of heterogeneous functional blocks, our approach provides efficient power savings by dynamically scheduling the scaling of voltage and frequency at the same time. Simulation results indicate that by using heuristic based strategies significant power savings can be achieved

NASA Space Engineering Research Center for VLSI systems design

This annual review reports the center's activities and findings on very large scale integration (VLSI) systems design for 1990, including project status, financial support, publications, the NASA Space Engineering Research Center (SERC) Symposium on VLSI Design, research results, and outreach programs. Processor chips completed or under development are listed. Research results summarized include a design technique to harden complementary metal oxide semiconductors (CMOS) memory circuits against single event upset (SEU); improved circuit design procedures; and advances in computer aided design (CAD), communications, computer architectures, and reliability design. Also described is a high school teacher program that exposes teachers to the fundamentals of digital logic design

The COMPLEX reference framework for HW/SW co-design and power management supporting platform-based design-space exploration

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Optimizing the Use of Behavioral Locking for High-Level Synthesis

The globalization of the electronics supply chain requires effective methods to thwart reverse engineering and IP theft. Logic locking is a promising solution, but there are many open concerns. First, even when applied at a higher level of abstraction, locking may result in significant overhead without improving the security metric. Second, optimizing a security metric is application-dependent and designers must evaluate and compare alternative solutions. We propose a meta-framework to optimize the use of behavioral locking during the high-level synthesis (HLS) of IP cores. Our method operates on chip’s specification (before HLS) and it is compatible with all HLS tools, complementing industrial EDA flows. Our meta-framework supports different strategies to explore the design space and to select points to be locked automatically. We evaluated our method on the optimization of differential entropy, achieving better results than random or topological locking: 1) we always identify a valid solution that optimizes the security metric, while topological and random locking can generate unfeasible solutions; 2) we minimize the number of bits used for locking up to more than 90% (requiring smaller tamper-proof memories); 3) we make better use of hardware resources since we obtain similar overheads but with higher security metric

Testability considerations for implementing an embedded memory subsystem

textThere are a number of testability considerations for VLSI design, but test coverage, test time, accuracy of test patterns and correctness of design information for DFD (Design for debug) are the most important ones in design with embedded memories. The goal of DFT (Design-for-Test) is to achieve zero defects. When it comes to the memory subsystem in SOCs (system on chips), many flavors of memory BIST (built-in self test) are able to get high test coverage in a memory, but often, no proper attention is given to the memory interface logic (shadow logic). Functional testing and BIST are the most prevalent tests for this logic, but functional testing is impractical for complicated SOC designs. As a result, industry has widely used at-speed scan testing to detect delay induced defects. Compared with functional testing, scan-based testing for delay faults reduces overall pattern generation complexity and cost by enhancing both controllability and observability of flip-flops. However, without proper modeling of memory, Xs are generated from memories. Also, when the design has chip compression logic, the number of ATPG patterns is increased significantly due to Xs from memories. In this dissertation, a register based testing method and X prevention logic are presented to tackle these problems. An important design stage for scan based testing with memory subsystems is the step to create a gate level model and verify with this model. The flow needs to provide a robust ATPG netlist model. Most industry standard CAD tools used to analyze fault coverage and generate test vectors require gate level models. However, custom embedded memories are typically designed using a transistor-level flow, there is a need for an abstraction step to generate the gate models, which must be equivalent to the actual design (transistor level). The contribution of the research is a framework to verify that the gate level representation of custom designs is equivalent to the transistor-level design. Compared to basic stuck-at fault testing, the number of patterns for at-speed testing is much larger than for basic stuck-at fault testing. So reducing test and data volume are important. In this desertion, a new scan reordering method is introduced to reduce test data with an optimal routing solution. With in depth understanding of embedded memories and flows developed during the study of custom memory DFT, a custom embedded memory Bit Mapping method using a symbolic simulator is presented in the last chapter to achieve high yield for memories.Electrical and Computer Engineerin