6 research outputs found

    A Novel Basis for Logic Rewriting

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    Given a set of logic primitives and a Boolean function, exact synthesis finds the optimum representation (e.g., depth or size) of the function in terms of the primitives. Due to its high computational complexity, the use of exact synthesis is limited to small networks. Some logic rewriting algorithms use exact synthesis to replace small subnetworks by their optimum representations. However, conventional approaches have two major drawbacks. First, their scalability is limited, as Boolean functions are enumerated to precompute their optimum representations. Second, the strategies used to replace subnetworks are not satisfactory. We show how the use of exact synthesis for logic rewriting can be improved. To this end, we propose a novel method that includes various improvements over conventional approaches: (i) we improve the subnetwork selection strategy, (ii) we show how enumeration can be avoided, allowing our method to scale to larger subnetworks, and (iii) we introduce XOR Majority Graphs (XMGs) as compact logic representations that make exact synthesis more efficient. We show a 45.8% geometric mean reduction (taken over size, depth, and switching activity), a 6.5% size reduction, and depth · size reductions of 8.6%, compared to the academic state-of-the-art. Finally, we outperform 3 over 9 of the best known size results for the EPFL benchmark suite, reducing size by up to 11.5% and depth up to 46.7%

    Cost Effective Implementation of Fixed Point Adders for LUT based FPGAs using Technology Dependent Optimizations

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    Modern day field programmable gate arrays (FPGAs) have very huge and versatile logic resources resulting in the migration of their application domain from prototype designing to low and medium volume production designing. Unfortunately most of the work pertaining to FPGA implementations does not focus on the technology dependent optimizations that can implement a desired functionality with reduced cost. In this paper we consider the mapping of simple ripple carry fixed-point adders (RCA) on look-up table (LUT) based FPGAs. The objective is to transform the given RCA Boolean network into an optimized circuit netlist that can implement the desired functionality with minimum cost. We particularly focus on 6-input LUTs that are inherent in all the modern day FPGAs. Technology dependent optimizations are carried out to utilize this FPGA primitive efficiently and the result is compared against various adder designs. The implementation targets the XC5VLX30-3FF324 device from Xilinx Virtex-5 FPGA family. The cost of the circuit is expressed in terms of the resources utilized, critical path delay and the amount of on-chip power dissipated. Our implementation results show a reduction in resources usage by at least 50%; increase in speed by at least 10% and reduction in dynamic power dissipation by at least 30%. All this is achieved without any technology independent (architectural) modification

    Post-mapping Topology Rewriting for FPGA Area Minimization

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    Circuit designers require Computer-Aided Design (CAD) tools when compiling designs into Field Programmable Gate Arrays (FPGAs) in order to achieve high quality results due to the complexity of the compilation tasks involved. Technology mapping is one critical step in the FPGA CAD flow. The final mapping result has significant impact on the subsequent steps of clustering, placement and routing, for the objectives of delay, area and power dissipation. While depth-optimal FPGA technology mapping can be solved in polynomial time, area minimization has proven to be NP-hard. Most modern state-of-the-art FPGA technology mappers are structural in nature; they are based on cut enumeration and use various heuristics to yield depth and area minimized solutions. However, the results produced by structural technology mappers rely strongly on the structure of the input netlists. Hence, it is common to apply additional heuristics after technology mapping to further optimize area and reduce the amount of structural bias while not harming depth. Recently, SAT-based Boolean matching has been used for post-mapping area minimization. However, SAT-based matching is computationally complex and too time consuming in practice. This thesis proposes an alternative Boolean matching approach based on NPN equivalence. Using a library of pre-computed topologies, the matching problem becomes as simple as performing NPN encoding followed by a hash lookup which is very efficient. In conjunction with Ashenhurst decomposition, the NPN-based Boolean matching is allowed to handle up to 10-input Boolean functions. When applied to a large set of designs, the proposed algorithm yields, on average, more than 3% reduction in circuit area without harming circuit depth. The priori generation of a library of topologies can be difficult; the potential difficulty in generating a library of topologies represents one limitation of the proposed algorithm

    Beyond the arithmetic constraint: depth-optimal mapping of logic chains in reconfigurable fabrics

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    Look-up table based FPGAs have migrated from a niche technology for design prototyping to a valuable end-product component and, in some cases, a replacement for general purpose processors and ASICs alike. One way architects have bridged the performance gap between FPGAs and ASICs is through the inclusion of specialized components such as multipliers, RAM modules, and microcontrollers. Another dedicated structure that has become standard in reconfigurable fabrics is the arithmetic carry chain. Currently, it is only used to map arithmetic operations as identified by HDL macros. For non-arithmetic operations, it is an idle but potentially powerful resource.;Obstacles to using the carry chain for generic logic operations include lack of architectural and computer-aided design support. Current carry-select architectures facilitate carry chain reuse, although they do so only for (K-1)-input operations. Additionally, hardware description language (HDL) macros are the only recourse for a designer wishing to map generic logic chains in a carry-select architecture. A novel architecture that allows the full K-input operational capacity of the carry chain to be harnessed is presented as a solution to current architectural limitations. It is shown to have negligible impact on logic element area and delay. Using only two additional 2:1 pass transistor multiplexers, it enables the transmission of a K-input operation to the carry chain and general routing simultaneously. To successfully identify logic chains in an arbitrary Boolean network, ChainMap is presented as a novel technology mapping algorithm. ChainMap creates delay-optimal generic logic chains in polynomial time without HDL macros. It maps both arithmetic and non-arithmetic logic chains whenever depth increasing nodes, which increase logic depth but not routing depth, are encountered. Use of the chain is not reserved for arithmetic, but rather any set of gates exhibiting similar characteristics. By using the carry chain as a generic, near zero-delay adjacent cell interconnection structure a potential average optimal speedup of 1.4x is revealed. Post place and route experiments indicate that ChainMap solutions perform similarly to HDL chains when cluster resources are abundant and significantly better in cluster-constrained arrays
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