240 research outputs found
OPTIMIZING LARGE COMBINATIONAL NETWORKS FOR K-LUT BASED FPGA MAPPING
Optimizing by partitioning is a central problem in VLSI design automation, addressing circuit’s manufacturability. Circuit partitioning has multiple applications in VLSI design. One of the most common is that of dividing combinational circuits (usually large ones) that will not fit on a single package among a number of packages. Partitioning is of practical importance for k-LUT based FPGA circuit implementation. In this work is presented multilevel a multi-resource partitioning algorithm for partitioning large combinational circuits in order to efficiently use existing and commercially available FPGAs packagestwo-way partitioning, multi-way partitioning, recursive partitioning, flat partitioning, critical path, cutting cones, bottom-up clusters, top-down min-cut
FGPGA: An Efficient Genetic Approach for Producing Feasible Graph Partitions
Graph partitioning, a well studied problem of parallel computing has many
applications in diversified fields such as distributed computing, social
network analysis, data mining and many other domains. In this paper, we
introduce FGPGA, an efficient genetic approach for producing feasible graph
partitions. Our method takes into account the heterogeneity and capacity
constraints of the partitions to ensure balanced partitioning. Such approach
has various applications in mobile cloud computing that include feasible
deployment of software applications on the more resourceful infrastructure in
the cloud instead of mobile hand set. Our proposed approach is light weight and
hence suitable for use in cloud architecture. We ensure feasibility of the
partitions generated by not allowing over-sized partitions to be generated
during the initialization and search. Our proposed method tested on standard
benchmark datasets significantly outperforms the state-of-the-art methods in
terms of quality of partitions and feasibility of the solutions.Comment: Accepted in the 1st International Conference on Networking Systems
and Security 2015 (NSysS 2015
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Back-annotation for interactive data path synthesis
In order to take into account physical design effects, a designer needs a feedback mechanism during interactive data path synthesis. In this paper, we propose a hypergraph model and a back-annotation algorithm which provide a feedback mechanism for back-annotation from physical designs to behavioral descriptions. Given a control data flow graph and its structural design, this back-annotation technique cannot only evaluate the design quality but can also feedback the delay to each edge and node in the graph. Therefore, a designer can identify the critical paths and improve the design. The hypergraph model and the back-annotation algorithm allow us to bridge the gap between the behavioral description and the physical design
Simulated Annealing Approach onto VLSI Circuit Partitioning
Decompositions of inter-connected components, to achieve modular independence, poses the major problem in VLSI circuit partitioning. This problem is intractable in nature, Solutions of these problems in computational science is possible through appropriate heuristics. Reduction of the cost that occurs due to interconnectivity between several VLSI components is referred to in this paper. Modification of results derived by classical iterative procedures with probabilistic methods is attempted. Verification has been done on ISCAS-85 benchmark circuits. The proposed design tool shows remarkable improvement results in comparison to the traditional one when applied to the standard benchmark circuits like ISCAS-85
A High-Performance Triple Patterning Layout Decomposer with Balanced Density
Triple patterning lithography (TPL) has received more and more attentions
from industry as one of the leading candidate for 14nm/11nm nodes. In this
paper, we propose a high performance layout decomposer for TPL. Density
balancing is seamlessly integrated into all key steps in our TPL layout
decomposition, including density-balanced semi-definite programming (SDP),
density-based mapping, and density-balanced graph simplification. Our new TPL
decomposer can obtain high performance even compared to previous
state-of-the-art layout decomposers which are not balanced-density aware, e.g.,
by Yu et al. (ICCAD'11), Fang et al. (DAC'12), and Kuang et al. (DAC'13).
Furthermore, the balanced-density version of our decomposer can provide more
balanced density which leads to less edge placement error (EPE), while the
conflict and stitch numbers are still very comparable to our
non-balanced-density baseline
Beyond pairwise clustering
We consider the problem of clustering in domains where the affinity relations are not dyadic (pairwise), but rather triadic, tetradic or higher. The problem is an instance of the hypergraph partitioning problem. We propose a two-step algorithm for solving this problem. In the first step we use a novel scheme to approximate the hypergraph using a weighted graph. In the second step a spectral partitioning algorithm is used to partition the vertices of this graph. The algorithm is capable of handling hyperedges of all orders including order two, thus incorporating information of all orders simultaneously. We present a theoretical analysis that relates our algorithm to an existing hypergraph partitioning algorithm and explain the reasons for its superior performance. We report the performance of our algorithm on a variety of computer vision problems and compare it to several existing hypergraph partitioning algorithms
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