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Even though enumeration is a common technique adapted in very large-scale integration (VLSI) floorplanning, its impact in terms of wirelength, whitespace, as well as runtime on the floorplanning has never been investigated comprehensively. In this study, enumerative floorplanner (EFP) is proposed here by using enumeration. The impact of the maximum enumeration order on VLSI floorplan layout is investigated and the tradeoff relationship with the wirelength, area and runtime is analysed as well. In EFP, dynamic programming enumerative clustering (DEC) technique is employed to reduce the worst-case time complexity and runtime. DEC also introduces the same number of possible permutations of modules while reducing the redundancy created in enumerative clustering (EC) without the usage of dynamic programming. A straightforward cost function is adapted to assist DEC to select the best cluster permutation, and a rigorous local refinement is proposed to compensate the EC's impact on the floorplan wirelength. Experimental results show that EFP is a high performance floorplanner when compared to existing methods in terms of robustness, scalability and stability.

From the industrial perspective, floorplanning is a crucial step in the VLSI physical design process as its efficiency determines the quality and the time-to-market of the product. A new perturbation method, called Cull-and-Aggregate Bottom-up Floorplanner (CABF), which consists of culling and aggregating stages, is developed to perform variable-order automated floorplanning for VLSI. CABF will generate VLSI floorplan layout by calculating the modules' dimensions' differences (hard module floorplanning problems) and the modules' areas' differences (soft module floorplanning problems). Through mathematical derivation, the hard modules floorplanning area minimization cost function (two-dimensional) during culling stage is proven that a dimensional reduction can be carried out to be the difference-based cost function (one-dimensional) which simplifies the computation. During the culling stage, CABF employs linear ordering method to select and determine the order of modules where this linear runtime complexity property allows CABF to cull the modules faster. The aggregating stage of CABF will reduce the subsequent search space of this floorplanner, and the variable order aggregation enables CABF to search for the best near-optimal solution. Based on Gigascale Systems Research Center and Microelectronics Center of North Carolina circuit benchmarks, CABF gives better optimal solutions and faster runtimes for floorplanning problems involving 9 to 600 modules. This has established that CABF is performing well in respect of reliability and scalability. Besides, CABF shows its potential to be implemented in VLSI physical design as the runtime of CABF is faster with a near-optimal outcome as compared to the other existing algorithms.

Placement is important in VLSI physical design as it determines the time-to-market and chip's reliability. In this paper, a new floorplan representation which couples with Ant System, namely Corner Insertion Sequence (CIS) is proposed. Though CIS's search complexity is smaller than the state-of-the-art representation Corner Sequence (CS), CIS adopts a preset boundary on the placement and hence, leading to search bound similar to CS. This enables the previous unutilized corner edges to become viable. Also, the redundancy of CS representation is eliminated in CIS leads to a lower search complexity of CIS. Experimental results on Microelectronics Center of North Carolina (MCNC) hard block benchmark circuits show that the proposed algorithm performs comparably in terms of area yet at least two times faster than CS