Synthesis of a Compositional Microprogram Control Unit with Two Cores of Partial Functions
DOI:
https://doi.org/10.15407/intechsys.2026.03.015Keywords:
partial function, kernel, CMCU, LUT, EMB, synthesys, structural decompositionAbstract
Introduction. Digital systems consist of combinational and sequential blocks. The most important sequential blocks include control units (CU). The circuits of CUs are not standard library components in CAD systems, so designing a particular CU circuit is a more labor-intensive process than implementing systems from common blocks such as registers, counters, arithmetic blocks, and logic blocks.
The quality of a digital system depends on the optimal characteristics of the CU. When synthesizing a CU circuit, it is necessary to solve a number of optimization problems: reducing the chip area occupied by the CU, increasing performance, and reducing power consumption. It is believed that solving the first of these problems allows improving other characteristics of the CU circuit.
Purpose of the work. The main focus of this article is the development of effective methods for optimizing the parameters of CU circuits when implemented on an FPGA (field-programmable gate array) basis.
Methods. A method for structural decomposition of a Compositional Microprogram Control Unit (CMCU) circuit in an FPGA is proposed. The method is based on the identification of two cores of partial functions. One core is based on the functional decomposition and generates functions for which the number of arguments exceeds the number of LUT inputs. The second core is based on the adaptation of twofold state assignments methods to the specifics of CMCU. This core generates functions based on the encoding of operator linear chains.
Results. An CMCU architecture with two cores of partial functions and a method for synthesizing the CMCU circuit are proposed. The FPGA implementation of the CMCU circuit used look-up tables (LUTs) and embedded memory blocks (EMBs). Since AMD Xilinx is the dominant FPGA chip manufacturer, the method proposed in this article is tailored to FPGAs from this company.
An example of synthesizing a CMCU circuit with two cores is presented. The conditions for applying this approach are discussed. Possible solutions to optimization problems associated with imbalances in the characteristics of the control algorithm and LUT elements are demonstrated.
Conclusion. During the synthesis of a CMCU with two cores of partial functions, a number of optimization problems arise. This is necessitated by an imbalance between: 1) the number of classes in the operator linear chains set partitioning and the number of LUT element inputs, and 2) the number of address variables and the number of LUT element inputs. This article analyzes these situations and identifies the corresponding conditions. In our future research, we intend to develop a method for mitigating the impact of these factors.
References
Barkalov A., Titarenko L. Logic Synthesis for Compositional Microprogram Control Units. Lectures Notes in Electrical Engineering, Springer, 2008, Vol. 22, 272 p. https://doi.org/10.1007/978-3-540-69285-0
Barkalov A. Microprogram control unit as composition of automate with programmable and hardwired logic. Automatics and Computer Science, 1983, Vol. 17, 36–41.
Feng W., Greene J., Mishchenko A. Improving FPGA Performance with a S44 LUT Structure. ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (NewYork,NY,USA), FPGA’18, 2018, Association for Computing Machinery, 61–66. https://doi.org/10.1145/3174243.317427
Kuon I., Tessier R., Rose J. FPGA Architecture: Survey and Challenges. Foundations and Trends in Electronic Design Automation, 2008, Vol 2 (2), 135–253. https://doi.org/10.1561/1000000005
DeMicheli G. Synthesis and optimization of digital circuits. New York: McGraw-Hill, 1994, 576 p.
Ruiz-Rosero J., Ramirez-Gonzalez G., Khanna R. Field Programmable Gate Array Applications—A Scientometric Review. Computation, 2019, Vol. 7 (4), Article 63. https://doi.org/10.3390/computation7040063
Czerwinski R., Kania D. Synthesis method of high speed finite state machines. Bulletin of the polish academy of sciences. Technical sciences, 2010, Vol. 58 (4), 635–644. https://doi.org/10.2478/v10175-010-0067-6
Kubica M., Opara A., Kania D. Technology Mapping for LUT- based. FPGA. Springer, 2021. https://doi.org/10.1007/978-3-030-60488-2
Barkalov A., Titarenko L., Mielcarek K., Chmielewski S. Logic Synthesis for FPGA–Based Control Units. Structural Decomposition in Logic Design. Lecture Notes in Electrical Engineering, Springer, 2020, Vol. 636. https://doi.org/10.1007/978-3-030-38295-7
Grout I. Digital systems design with FPGAs and CPLDs. Elsevier, Amsterdam, 2008, 784 p. https://doi.org/10.1016/B978-0-7506-8397-5.X0001-3
Barkalov O., Titarenko L., Saburova S., Golovin, O., V. Matvienko O. Optimization of a composite microprogram control device scheme with a basic architecture. Cybernetics and Computer Technologies, 2024, Issue 4, 121–133. https://doi.org/10.34229/2707-451X.24.4.11
Baranov S. Logic synthesis for control automata. Dordrecht: Kluwer Academic Publishers, 1994, 312 p. https://doi.org/10.1007/978-1-4615-2692-6
Chapman K. Multiplexer Design Techniques for Datapath Performance with Minimized Routing Resources. Xilinx All Programmable, 2014. URL: https://docs.amd.com/api/khub/documents/9pOn~3NV8ApAbwglqp6MJQ/content [Accessed Jan. 2022]
Trimberg S. Three ages of FPGA: A retrospective on the first thirty years of FPGA technology. IEEE Proceedings 103, 2015, Vol. 3, 318–331. https://doi.org/10.1109/JPROC.2015.2392104
Tiwari A., Tomko K. Saving power by mapping finite state machines into embedded memory blocks in FPGAs. Design, Automation and Test in Europe Conference and Exhibition, Paris, France, 2004, Vol. 2, 916–921. https://doi.org/10.1109/DATE.2004.1269007
Senhaji-Navarro R., Garcia-Vargas I., Jimenes-Moreno G., Civit-Balcells A., Guerra-Gutierres P. ROM-based FSM implementation using input multiplexing in FPGA devices. Electronics Letters, 2004, Vol. 40 (20), 1249–1251. https://doi.org/10.1049/el:20046007
Xilinx. URL: https://www.amd.com/en/products/adaptive-socs-and-fpgas/fpga.html#overview [Accessed Jan. 2025]
Vivado Design Suite. URL: https://www.xilinx.com/products/design-tools/vivado.html,2020 [Accessed Jan. 2025]
Quartus II. URL: https://www.intel.com/content/www/us/en/products/details/fpga/development-tools/quartus-prime/resource.html [Accessed Jan. 2025]
Barkalov O., Titarenko L., Mielcarek K. Hardware reduction for LUT based Mealy FSMs. International Journal of Applied Mathematics and Computer Science, 2018, Vol. 28 (3), 595–607. https://doi.org/10.2478/amcs-2018-0046
Barkalov A., Titarenko L., Mielcarek K. Hardware reduction for LUT–based Mealy FSMs. International Journal of Applied Mathematics and Computer Science, 2018, Vol. 28 (3), 595–607. https://doi.org/10.2478/amcs-2018-0046
Opara A., Kubica M., Kania D. Decomposition Approaches for Power Reduction. IEEE Access, 2023, Vol. 11, 29417–29429. https://doi.org/10.1109/ACCESS.2023.3260970
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