Instruction Set Optimization for FM-Type Digital Signal Processor (DSP) Architectures

The efficiency of modern digital signal processors (DSPs) is heavily influenced by the design and optimization of their instruction sets. This paper presents a comprehensive study on instruction set optimization strategies tailored for FM-type DSP architectures, which are characterized by parallel data and instruction processing capabilities. As signal processing demands continue to escalate in communication, audio, and embedded systems, the need for streamlined, energy-efficient, and high-throughput DSP architectures becomes paramount. The FM-type DSP architecture offers inherent advantages in instruction-level parallelism (ILP) and data-level parallelism (DLP); however, without a well-optimized instruction set, these benefits may remain underutilized. The proposed optimization framework focuses on reducing instruction redundancy, improving compiler scheduling, and enhancing the mapping of high-level. DSP algorithms into hardware-efficient assembly instructions. Key techniques explored include instruction fusion, macro-instruction encoding, and custom instruction set extensions for multiply-accumulate (MAC) and vector operations. Furthermore, this research investigates instruction pipeline balancing to mitigate hazards, minimize latency, and achieve maximum instruction throughput. Simulation results using benchmark DSP applications, such as digital filtering and GSM channel encoding, demonstrate performance improvements of up to 30% in execution time and 25% in power efficiency compared to baseline FM-DSP configurations. The study also highlights the importance of hardware-software co-design, wherein compiler tools and hardware architecture are co-optimized to exploit parallelism and minimize control overhead. This co-design methodology ensures that instruction scheduling, loop unrolling, and memory access patterns are fully aligned with the FM architecture’s unique structure. Additionally, the paper discusses how instruction optimization contributes to overall system scalability, especially for real-time and multi-core DSP implementations. In conclusion, instruction set optimization is a critical enabler of performance in FM-type DSP architectures. The findings underscore that efficient instruction encoding, reduced control complexity, and architectural awareness can significantly enhance computational throughput while reducing energy consumption, making FM-DSPs more suitable for next-generation signal processing applications.