Enhanced Design of Resource-Efficient Approximate Multipliers with Truncation and Error Compensation for Multimedia Applications

Abstract

Approximate computing offers an effective strategy for reducing resource utilization in multiplier design, particularly in applications where tolerance for errors is essential, such as multimedia and signal processing. This paper presents a systematic approach for designing an efficient 8x8 approximate multiplier by integrating truncation, approximation, and exact computation at various stages of partial product generation. This approach employs approximate compressors to streamline partial product decomposition, achieving significant reductions in hardware complexity, power consumption, and latency while maintaining acceptable accuracy levels. Additionally, error compensation techniques are applied to minimize discrepancies arising from approximations and truncations. A key innovation is the use of single-stage decomposition with higher-order compressors, which reduces operating time by handling all partial product decompositions in a single stage. For scalability, a 16x16 multiplier is constructed using a four-row parallel arrangement of proposed 8x8 multipliers, combining exact and approximate designs for enhancing efficiency. The proposed 16x16 multiplier design achieves a 30% reduction in delay, 15% lower power consumption, a 40.3% reduction in Power-Delay Product (PDP), and occupies 14.4% less area compared to the nearest existing designs, underscoring its superior efficiency and performance. The proposed design also significantly outperforms existing designs in error analysis metrics, showcasing improved accuracy and quality while ensuring high efficiency. This design methodology offers an optimal balance between accuracy and resource efficiency, making it an effective solution for resource-constrained, error-tolerant applications.