4,647 research outputs found
Parametric Yield of VLSI Systems under Variability: Analysis and Design Solutions
Variability has become one of the vital challenges that the
designers of integrated circuits encounter. variability becomes
increasingly important. Imperfect manufacturing process manifest
itself as variations in the design parameters. These variations
and those in the operating environment of VLSI circuits result in
unexpected changes in the timing, power, and reliability of the
circuits. With scaling transistor dimensions, process and
environmental variations become significantly important in the
modern VLSI design. A smaller feature size means that the physical
characteristics of a device are more prone to these
unaccounted-for changes. To achieve a robust design, the random
and systematic fluctuations in the manufacturing process and the
variations in the environmental parameters should be analyzed and
the impact on the parametric yield should be addressed.
This thesis studies the challenges and comprises solutions for
designing robust VLSI systems in the presence of variations.
Initially, to get some insight into the system design under
variability, the parametric yield is examined for a small circuit.
Understanding the impact of variations on the yield at the circuit
level is vital to accurately estimate and optimize the yield at
the system granularity. Motivated by the observations and results,
found at the circuit level, statistical analyses are performed,
and solutions are proposed, at the system level of abstraction, to
reduce the impact of the variations and increase the parametric
yield.
At the circuit level, the impact of the supply and threshold
voltage variations on the parametric yield is discussed. Here, a
design centering methodology is proposed to maximize the
parametric yield and optimize the power-performance trade-off
under variations. In addition, the scaling trend in the yield loss
is studied. Also, some considerations for design centering in the
current and future CMOS technologies are explored.
The investigation, at the circuit level, suggests that the
operating temperature significantly affects the parametric yield.
In addition, the yield is very sensitive to the magnitude of the
variations in supply and threshold voltage. Therefore, the spatial
variations in process and environmental variations make it
necessary to analyze the yield at a higher granularity. Here,
temperature and voltage variations are mapped across the chip to
accurately estimate the yield loss at the system level.
At the system level, initially the impact of process-induced
temperature variations on the power grid design is analyzed. Also,
an efficient verification method is provided that ensures the
robustness of the power grid in the presence of variations. Then,
a statistical analysis of the timing yield is conducted, by taking
into account both the process and environmental variations. By
considering the statistical profile of the temperature and supply
voltage, the process variations are mapped to the delay variations
across a die. This ensures an accurate estimation of the timing
yield. In addition, a method is proposed to accurately estimate
the power yield considering process-induced temperature and supply
voltage variations. This helps check the robustness of the
circuits early in the design process.
Lastly, design solutions are presented to reduce the power
consumption and increase the timing yield under the variations. In
the first solution, a guideline for floorplaning optimization in
the presence of temperature variations is offered. Non-uniformity
in the thermal profiles of integrated circuits is an issue that
impacts the parametric yield and threatens chip reliability.
Therefore, the correlation between the total power consumption and
the temperature variations across a chip is examined. As a result,
floorplanning guidelines are proposed that uses the correlation to
efficiently optimize the chip's total power and takes into account
the thermal uniformity.
The second design solution provides an optimization methodology
for assigning the power supply pads across the chip for maximizing
the timing yield. A mixed-integer nonlinear programming (MINLP)
optimization problem, subject to voltage drop and current
constraint, is efficiently solved to find the optimum number and
location of the pads
Statistical Power Supply Dynamic Noise Prediction in Hierarchical Power Grid and Package Networks
One of the most crucial high performance systems-on-chip design challenge is to front their power supply noise sufferance due to high frequencies, huge number of functional blocks and technology scaling down. Marking a difference from traditional post physical-design static voltage drop analysis, /a priori dynamic voltage drop/evaluation is the focus of this work. It takes into account transient currents and on-chip and package /RLC/ parasitics while exploring the power grid design solution space: Design countermeasures can be thus early defined and long post physical-design verification cycles can be shortened. As shown by an extensive set of results, a carefully extracted and modular grid library assures realistic evaluation of parasitics impact on noise and facilitates the power network construction; furthermore statistical analysis guarantees a correct current envelope evaluation and Spice simulations endorse reliable result
Nano-Sim: A Step Wise Equivalent Conductance based Statistical Simulator for Nanotechnology Circuit Design
New nanotechnology based devices are replacing CMOS devices to overcome CMOS
technology's scaling limitations. However, many such devices exhibit
non-monotonic I-V characteristics and uncertain properties which lead to the
negative differential resistance (NDR) problem and the chaotic performance.
This paper proposes a new circuit simulation approach that can effectively
simulate nanotechnology devices with uncertain input sources and negative
differential resistance (NDR) problem. The experimental results show a 20-30
times speedup comparing with existing simulators.Comment: Submitted on behalf of EDAA (http://www.edaa.com/
Resilient Design for Process and Runtime Variations
The main objective of this thesis is to tackle the impact of parameter variations in order to improve the chip performance and extend its lifetime
CAD Techniques for Robust FPGA Design Under Variability
The imperfections in the semiconductor fabrication process and uncertainty in operating environment of VLSI circuits have emerged as critical challenges for the semiconductor industry. These are generally termed as process and environment variations, which lead to uncertainty in
performance and unreliable operation of the circuits. These problems have been
further aggravated in scaled nanometer technologies due to increased process
variations and reduced operating voltage.
Several techniques have been proposed recently for designing digital VLSI circuits
under variability. However, most of them have targeted ASICs and custom designs.
The flexibility of reconfiguration and unknown end application in FPGAs
make design under variability different for FPGAs compared to
ASICs and custom designs, and the techniques proposed for ASICs and custom designs cannot be directly applied
to FPGAs. An important design consideration is to minimize the modifications in architecture and circuit
to reduce the cost of changing the existing FPGA architecture and circuit.
The focus of this work can be divided into three principal categories, which are, improving
timing yield under process variations, improving power yield under process variations and improving the voltage profile
in the FPGA power grid.
The work on timing yield improvement proposes routing architecture enhancements along with CAD techniques to
improve the timing yield of FPGA designs. The work on power yield improvement for FPGAs selects a low power dual-Vdd FPGA design
as the baseline FPGA architecture for developing power yield enhancement techniques. It proposes CAD techniques to improve the
power yield of FPGAs. A mathematical programming technique is proposed to determine the parameters
of the buffers in the interconnect such as the sizes of the transistors and threshold voltage of the transistors, all
within constraints, such that the leakage variability is minimized under delay constraints.
Two CAD techniques are investigated and proposed to improve the supply voltage profile of
the power grids in FPGAs. The first technique is a place and route technique and the second technique
is a logic clustering technique to reduce IR-drops and spatial variation of supply voltage in the power grid
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
Toward Reliable, Secure, and Energy-Efficient Multi-Core System Design
Computer hardware researchers have perennially focussed on improving the performance of computers while stipulating the energy consumption under a strict budget. While several innovations over the years have led to high performance and energy efficient computers, more challenges have also emerged as a fallout. For example, smaller transistor devices in modern multi-core systems are afflicted with several reliability and security concerns, which were inconceivable even a decade ago. Tackling these bottlenecks happens to negatively impact the power and performance of the computers. This dissertation explores novel techniques to gracefully solve some of the pressing challenges of the modern computer design. Specifically, the proposed techniques improve the reliability of on-chip communication fabric under a high power supply noise, increase the energy-efficiency of low-power graphics processing units, and demonstrate an unprecedented security loophole of the low-power computing paradigm through rigorous hardware-based experiments
Cross-Layer Resiliency Modeling and Optimization: A Device to Circuit Approach
The never ending demand for higher performance and lower power consumption pushes the VLSI industry to further scale the technology down. However, further downscaling of technology at nano-scale leads to major challenges. Reduced reliability is one of them, arising from multiple sources e.g. runtime variations, process variation, and transient errors. The objective of this thesis is to tackle unreliability with a cross layer approach from device up to circuit level
- …