35082628
Porosity-aware buffered Steiner tree construction
In order to achieve timing closure on increasingly complex IC designs, buffer insertion needs to be performed on thousands of nets within an integrated physical synthesis system. Modern designs may contain large blocks which severely constrain the buffer locations. Even when there may appear to be space for buffers in the alleys between large blocks, these regions are often densely packed or may be needed later to fix critical paths. Therefore, within physical synthesis, a buffer insertion scheme needs to be aware of the porosity of the existing layout to be able to decide when to insert buffers in dense regions to achieve critical performance improvement and when to utilize the sparser regions of the chip. This work addresses the problem of finding porosity-aware buffering solutions by constructing a "smart Steiner tree" to pass to van Ginneken's topology-based algorithm. This flow allows one to fully integrate the algorithm into a physical synthesis system without paying an exorbitant runtime penalty. We show that significant improvements on timing closure are obtained when this approach is integrated into a physical synthesis system.
28075982
Clock buffer polarity assignment for power noise reduction
1271597
An improved AMG-based method for fast power grid analysis
The continuing VLSI technology scaling leads to increasingly significant power supply fluctuations, which needs to be modeled accurately in circuit design and verification. Meanwhile, the huge size of power grid requires its analysis to be fast and highly scalable. Algebraic multigrid (AMG) has been recognized as a promising approach for fast power grid analysis. We propose several techniques to improve AMG-based power grid analysis: (1) dynamic reduction threshold; (2) weighted interpolation; and (3) a new error smoothing scheme. Experimental results on power grid with up to 1.6 million nodes show that these techniques can improve accuracy by over 10 times compared to a reported industrial method while retaining the same fast speed
7189153
Antenna avoidance in layer assignment
The sustained progress of very-large-scale-integration (VLSI) technology has dramatically increased the likelihood of the antenna problem in the manufacturing process and calls for corresponding considerations in the routing stage. In this paper, the authors propose a technique that can handle the antenna problem during the layer-assignment (LA) stage, which is an important step between global routing and detailed routing. The antenna-avoidance problem is modeled as a tree-partitioning problem with a linear-time-optimal-algorithm solution. This algorithm is customized to guide antenna avoidance in the LA stage. A linear-time optimal jumper-insertion algorithm is also derived. Experimental results on benchmark circuits show that the proposed techniques can lead to an average of 76% antenna-violation reduction and 99% via-violation reduction.
11408697
Path-Based Buffer Insertion
Along with the progress of very-large-scale-integration technology, buffer insertion plays an increasingly critical role on affecting circuit design and performance. Traditional buffer insertion algorithms are mostly net based and therefore often result in suboptimal delay or unnecessary buffer expense due to the lack of global view. In this paper, we propose a novel path-based-buffer-insertion (PBBI) scheme which can overcome the weakness of the net-based approaches. We also discuss some potential difficulties of the PBBI approach and propose solutions to them. A fast estimation on buffered delay is employed to improve the solution quality. Gate sizing is also considered at the same time. Experimental results show that our method can efficiently reduce buffer/gate cost significantly (by 71% on average) when compared to traditional net-based approaches. To the best of our knowledge, this is the first work on path based buffer insertion and simultaneous gate sizing.
10406726
Associative Skew Clock Routing for Difficult Instances
In clock network synthesis, sometimes skew constraints are required only within certain groups of clock sinks and do not exist between different groups. This is the so-called associative skew clock routing problem. Although the number of constraints is reduced, the problem becomes more difficult to solve due to the enlarged solution space. The perhaps only previous work used a very primitive delay model and cannot handle difficult instances in which sink groups are intermingled. We reuse existing techniques to solve this problem, including the difficult instances, based on a more accurate and popular delay model. Experimental results show that our algorithm can reduce the total clock routing wirelength by 12% on average compared to greedy-DME which is one of the best zero skew routing algorithms
17765935
Vector Processing Support for FPGA-Oriented High Performance Applications
In this paper, we propose and implement a vector processing system that includes two identical vector microprocessors embedded in two FPGA chips. Each vector microprocessor supports floating-point calculations and efficient sparse matrix operations. Dense matrix-matrix multiplication and sparse matrix-vector multiplication with benchmark matrices from various application domains were run on the system to evaluate its performance. The resulting calculation times are compared with those of a commercial PC to show the effectiveness of our approach.
16516558
Design and implementation of a CORBA-based genome mapping system prototype
MOTIVATION
CORBA (Common Object Request Broker Architecture), as an open standard, is considered to be a good solution for the development and deployment of applications in distributed heterogeneous environments. This technology can be applied in the bioinformatics area to enhance utilization, management and interoperation between biological resources.


RESULTS
This paper investigates issues in developing CORBA applications for genome mapping information systems in the Internet environment with emphasis on database connectivity and graphical user interfaces. The design and implementation of a CORBA prototype for an animal genome mapping database are described.


AVAILABILITY
The prototype demonstration is available via: http://www.ri.bbsrc.ac.uk/ark_corba/.


CONTACT
jian.hu@bbsrc.ac.uk
5276231
Open-ended robust design of analog filters using genetic programming
Most existing research on robust design using evolutionary algorithms (EA) follows the paradigm of traditional robust design, in which parameters of a design solution are tuned to improve the robustness of the system. However, the topological structure of a system may set a limit on the possible robustness achievable through parameter tuning. This paper proposes a new robust design paradigm that exploits the open-ended topological synthesis capability of genetic programming to evolve more robust systems. As a case study, a methodology for automated synthesis of dynamic systems, based on genetic programming and bond graph modeling (GPBG), is applied to evolve robust low-pass and high-pass analog filters. Compared with a traditional robust design approach based on a state-of-the-art real-parameter genetic algorithm (GA), it is shown that open-ended topology search by genetic programming with a fitness criterion rewarding robustness can evolve more robust systems with respect to parameter perturbations than what was achieved through parameter tuning alone, for our test problems.
8610229
System-Level Synthesis of MEMS via Genetic Programming and Bond Graphs
Initial results have been achieved for automatic synthesis of MEMS system-level lumped parameter models using genetic programming and bond graphs. This paper first discusses the necessity of narrowing the problem of MEMS synthesis into a certain specific application domain, e.g., RF MEM devices. Then the paper briefly introduces the flow of a structured MEMS design process and points out that system-level lumped-parameter model synthesis is the first step of the MEMS synthesis process. Bond graphs can be used to represent a system-level model of a MEM system. As an example, building blocks of RF MEM devices are selected carefully and their bond graph representations are obtained. After a proper and realizable function set to operate on that category of building blocks is defined, genetic programming can evolve both the topologies and parameters of corresponding RF MEM devices to meet predefined design specifications. Adaptive fitness definition is used to better direct the search process of genetic programming. Experimental results demonstrate the feasibility of the approach as a first step of an automated MEMS synthesis process. Some methods to extend the approach are also discussed.
15595451
HEMO: A Sustainable Multi-objective Evolutionary Optimization Framework
The capability of multi-objective evolutionary algorithms (MOEAs) to handle premature convergence is critically important when applied to real-world problems. Their highly multi-modal and discrete search space often makes the required performance out of reach to current MOEAs. Examining the fundamental cause of premature convergence in evolutionary search has led to proposing of a generic framework, named Hierarchical Fair Competition (HFC)[9], for robust and sustainable evolutionary search. Here an HFC-based Hierarchical Evolutionary Multi-objective Optimization framework (HEMO) is proposed, which is characterized by its simultaneous maintenance of individuals of all degrees of evolution in hierarchically organized repositories, by its continuous inflow of random individuals at the base repository, by its intrinsic hierarchical elitism and hyper-grid-based density estimation. Two experiments demonstrate its search robustness and its capability to provide sustainable evolutionary search for difficult multi-modal problems. HEMO makes it possible to do reliable multi-objective search without risk of premature convergence. The paradigmatic transition of HEMO to handle premature convergence is that instead of trying to escape local optima from converged high fitness populations, it tries to maintain the opportunity for new optima to emerge from the bottom up as enabled by its hierarchical organization of individuals of different fitnesses.