616 research outputs found
Algorithms for the scaling toward nanometer VLSI physical synthesis
Along the history of Very Large Scale Integration (VLSI), we have successfully scaled
down the size of transistors, scaled up the speed of integrated circuits (IC) and the number
of transistors in a chip - these are just a few examples of our achievement in VLSI scaling.
It is projected to enter the nanometer (timing estimation and buffer planning for global routing and other early stages such
as floorplanning. A novel path based buffer insertion scheme is also included, which
can overcome the weakness of the net based approaches. Part-2 Circuit clustering techniques with the application in Field-Programmable
Gate Array (FPGA) technology mapping
The problem of timing driven n-way circuit partitioning with application to FPGA
technology mapping is studied and a hierarchical clustering approach is presented for the latest multi-level FPGA architectures. Moreover, a more general delay model is included in order to accurately characterize the delay behavior of the clusters and circuit elements
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
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Nanometer VLSI placement and optimization for multi-objective design closure
In a VLSI physical synthesis flow, placement directly defines the interconnection,
which affects many other design objectives, such as timing, power consumption,
congestion, and thermal issues. With the scaling of technology, the relative interconnect
delay increases dramatically. As a result, placement has become a bottleneck
in deep sub-micron physical synthesis. In this dissertation, I propose several
optimization algorithms from global placement, placement migration, timing driven
placements, to incremental power optimizations for multi-objective VLSI design
closure. The first work is DPlace, a new global placement algorithm that scales
well to the modern large-scale circuit placement problems. DPlace simulates the
natural diffusion process to spread cells smoothly over the placement region, and
uses both analytical and discrete techniques to improve the wire length. However,
global placement is never sufficient for multi-objective design closure, a variety of
design objectives have to be improved incrementally, such as timing, routing congestion,
signal integrity, and heat distribution. Placement migration is a critical step
to address the cell overlaps appearing during incremental optimizations. To achieve
high placement stability, I propose a computational geometry based placement migration
flow to cope with placement changes, and a new stability metric to measure
the “similarity” between two placements accurately. Our placement migration algorithm
has clear advantage over conventional legalization algorithms such that the
neighborhood characteristics of the original placement are preserved. For timing
closure in high performance designs, I present a linear programming based incremental
timing driven placement to improve the timing on critical paths directly.
I further present an efficient timing driven placement algorithm (Pyramids). Two
formulations of Pyramids are proposed, which are suitable for different optimization
stages in a physical synthesis flow. Both approaches find the optimal location
for timing of a cell in constant time, through computational geometry based approaches.
For fast convergence of design closure, placement should be integrated
with other optimization techniques. I propose to combine placement, gate sizing
and Vt swapping techniques to reduce the total power consumption, especially the
leakage power, which is becoming increasingly critical for nanometer VLSI design
closure.Electrical and Computer Engineerin
A survey of system level power management schemes in the dark-silicon era for many-core architectures
Power consumption in Complementary Metal Oxide Semiconductor (CMOS) technology has escalated to a point that only a fractional part of many-core chips can be powered-on at a time. Fortunately, this fraction can be increased at the expense of performance through the dark-silicon solution. However, with many-core integration set to be heading towards its thousands, power consumption and temperature increases per time, meaning the number of active nodes must be reduced drastically. Therefore, optimized techniques are demanded for continuous advancement in technology. Existing efforts try to overcome this challenge by activating nodes from different parts of the chip at the expense of communication latency. Other efforts on the other hand employ run-time power management techniques to manage the power performance of the cores trading-off performance for power. We found out that, for a significant amount of power to saved and high temperature to be avoided, focus should be on reducing the power consumption of all the on-chip components. Especially, the memory hierarchy and the interconnect. Power consumption can be minimized by, reducing the size of high leakage power dissipating elements, turning-off idle resources and integrating power saving materials
Effective network grid synthesis and optimization for high performance very large scale integration system design
制度:新 ; 文部省報告番号:甲2642号 ; 学位の種類:博士(工学) ; 授与年月日:2008/3/15 ; 早大学位記番号:新480
Formal and Informal Methods for Multi-Core Design Space Exploration
We propose a tool-supported methodology for design-space exploration for
embedded systems. It provides means to define high-level models of applications
and multi-processor architectures and evaluate the performance of different
deployment (mapping, scheduling) strategies while taking uncertainty into
account. We argue that this extension of the scope of formal verification is
important for the viability of the domain.Comment: In Proceedings QAPL 2014, arXiv:1406.156
Master of Science
thesisAdvances in silicon photonics are enabling hybrid integration of optoelectronic circuits alongside current complementary metal-oxide-semiconductor (CMOS) technologies. To fully exploit the capability of this integration, it is important to explore the effects of thermal gradients on optoelectronic devices. The sensitivity of optical components to temperature variation gives rise to design issues in silicon on insulator (SOI) optoelectronic technology. The thermo-electric effect becomes problematic with the integration of hybrid optoelectronic systems, where heat is generated from electrical components. Through the thermo-optic effect, the optical signals are in turn affected and compensation is necessary. To improve the capability of optical SOI designs, optical-wave-simulation models and the characteristic thermal operating environment need to be integrated to ensure proper operation. In order to exploit the potential for compensation by virtue of resynthesis, temperature characterization on a system level is required. Thermal characterization within the flow of physical design automation tools for hybrid optoelectronic technology enables device resynthesis and validation at a system level. Additionally, thermally-aware routing and placement would be possible. A simplified abstraction will help in the active design process, within the contemporary computer-aided design (CAD) flow when designing optoelectronic features. This thesis investigates an abstraction model to characterize the effect of a temperature gradient on optoelectronic circuit operation. To make the approach scalable, reduced order computations are desired that effectively model the effect of temperature on an optoelectronic layout; this is achieved using an electrical analogy to heat flow. Given an optoelectronic circuit, using a thermal resistance network to abstract thermal flow, we compute the temperature distribution throughout the layout. Subsequently, we show how this thermal distribution across the optoelectronic system layout can be integrated within optoelectronic device- and system-level analysis tools
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