Computer Architecture, within Systems & Networks in the Computer & Information Sciences, is the discipline concerned with the structural, functional, and operational organization of computer systems. It examines how hardware components—processors, memory hierarchies, input/output subsystems, interconnects, and storage architectures—are designed, integrated, and optimized to execute computational tasks efficiently and reliably. Core areas include instruction set architecture (ISA), microarchitecture, pipelining, parallelism, cache design, branch prediction, multicore and many-core systems, vector and GPU architectures, and memory consistency models. Computer Architecture also encompasses performance evaluation, energy efficiency, hardware virtualization, accelerator design, and hardware–software co-optimization. As computing systems evolve toward heterogeneous architectures, distributed hardware, neuromorphic processors, and specialized accelerators for AI and cryptography, the field plays a central role in defining how computational capabilities scale, adapt, and meet the needs of modern applications.
Within the methodological framework of the Quantum Dictionary, Computer Architecture represents a domain where terminology is highly contextual, influenced by abstraction level, hardware design paradigm, execution model, and system constraints. Concepts such as “pipeline,” “cache,” “latency,” “throughput,” “instruction,” or “consistency” collapse into distinct semantic states depending on whether they are invoked in ISA specification, microarchitectural design, parallel processing, memory systems, or performance analysis. Terminological meaning also varies across architectures—superscalar, RISC, CISC, SIMD, MIMD, GPU, TPU, or FPGA-based systems—each exhibiting distinct structural and operational semantics. The quantum-semantic architecture encodes each hardware-related term as a contextual semantic entity whose meaning resolves according to system layer, architectural paradigm, workload characteristics, or optimization objective. This ensures semantic interoperability with adjacent fields such as operating systems, compilers, distributed systems, algorithms, and hardware engineering, while preserving the definitional precision required for correctness, performance modeling, and hardware–software integration. By modeling the interplay among hardware structures, control logic, computational models, and operational constraints, the Quantum Dictionary provides a coherent and adaptive lexicon aligned with the deeply technical and continually evolving nature of Computer Architecture.
