RADIOELECTRONIC AND COMPUTER SYSTEMS

The subject of study in this article is the models, methods, and principles of organization of entire lifecycle of Artificial Intelligence (AI) as a Service implemented with the use of Field Programmable Gate Array (FPGA). The purpose of this work is the improvement of the methodology of the deployment of dependable FPGA-based Artificial Intelligence as a Service by creating a complex of mutually agreed concept, principles, models, and methods considering the specifics of the use of heterogeneous computations of Artificial Intelligence and the possibility of realizing the unified protection of FPGA implementations. Tasks: to clarify the taxonomy of the dependability term within the proposed methodology; to propose the concept of deployment of dependable FPGA-based heterogeneous computations of Artificial Intelligence as a Service; to formulate the principle of tracing changes in FPGA projects and integrated environments during the entire lifecycle; to formulate the principle of unification of protection of FPGA implementations of heterogeneous computing of Artificial Intelligence as a Service; to formulate the principle of the product-service assessment of the availability of FPGA as a Service; and to discuss the promising directions of heterogeneous computations of AI. According to the tasks, the following results were obtained. The existing concepts of dependable systems deployment are discussed. The concept of the deployment of computations of Artificial Intelligence as a Service, which is obtained based on the improvement of paradigms of the creation and deployment of dependable systems and services, is proposed. The principle of tracing of changes, which assumes the updating of requirements during the lifecycle of FPGA projects, is proposed. The principle of the unification of protection, which combines and joins the consideration of various unique features of the FPGA instance to protect the implementation and the set of cyberthreats for the service as a whole, is proposed. The principle of the product-service assessment, which considers parameters and indicators of availability, is proposed. The perspective of the progress of non-electronic mediums for heterogeneous computations with the use of a photonic implementations of Artificial Intelligence computations to ensure improved performance and reduced energy consumption is discussed. Conclusions. One of the main contributions of this research is that in the proposed methodology, the set of principles, models, and methods of deployment of Artificial Intelligence as a Service under conditions of changing requirements and integrated environments, and the need for mechanism of licensing protection of each instance of the system are developed, which allows to reduce model uncertainty by considering various stages of the lifecycle of dependable FPGA implementation using heterogeneous computations.

dependability of AI; FPGA; tracing of changes; FPGA as a Service; unification of protection; DRM; Artificial Intelligence as a Service; AIaaS; hardware implementation of AI; heterogeneous computing for AI; product-service assessment; QoS; photonic AI

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