Aug 2026· Journal of Electrical Engineering· Vol 77, pp. 384 - 391· 0 citations· 21 references
TL;DR
A Radix-4 Carry-Save Adder (CSA) accumulator within the Radix-8 FSA MAC is presented and evaluated, achieving the best power-delay product (2204 pJ).
Abstract
Abstract Machine learning workloads impose extreme computational demands on hardware, driving the adoption of domain-specific accelerators built around Systolic Arrays (SAs). Factored Systolic Arrays (FSAs) based on Radix-8 Booth multiplications reduce multiplier complexity by relocating the encoding logic to the array periphery, thereby simplifying each Processing Element (PE). Despite this multiplier-side enhancement, the Multiply-Accumulate (MAC) unit’s accumulation stage continues to impose a critical bottleneck when implemented with a standard Ripple Carry Adder (RCA), whose carry-propagation delay scales linearly with the accumulator width. This paper presents a Radix-4 Carry-Save Adder (CSA) accumulator within the Radix-8 FSA MAC and evaluates it on the Xilinx Spartan-3E FPGA design suite 14.7. The proposed architecture significantly achieves 22.5%, 21.3%, 24.5% and 4.3% reductions in critical-path delay, LUT, Slice utilization and Power consumption relative to the RCA baseline. Further, as approximate computing has emerged as a promising solution for enhanced efficiency, a lower-part OR Adder variant is evaluated, achieving the best power-delay product (2204 pJ). Optimization within FSA MACs enables high-throughput Machine Learning acceleration.
Multiply–Accumulate (MAC) units dominate the arithmetic workload of digital signal processing, communication, image-processing, and machine-learning datapaths. Conventional MAC architectures often realize multiplication and accumulation as distinct hardware stages, typically combining an array multiplier with a ripple-...
Vasikarla Renuka, N. Bhavana, Bandla Sandhya· International Journal of Adv...· 0 citations
This work proposes a Precision-Reconfigurable Zero-Skipping SRAM-CIM (PRZS-CIM) architecture that combines bit-serial exact multiply-accumulate decomposition, 4/6/8-bit precision control, row-level zero gating, and all-zero bit-plane suppression.
Bitla Prabhakar T. Satyanarayana, Dr. Malothu Amru, Dr. Somala Rama Kishore· International Journal of Adv...· 0 citations
This work proposes Double-Duty, a logic block architecture that decouples LUTs and adder chains by augmenting four extra inputs of the logic element to bypass LUTs and directly drive the adders.
Xilai Dai, Junius Pun, Anthony Fei et al.· ACM Transactions on Reconfig...· 0 citations
The Proposed scheme achieved the lowest BF16-referenced Layer NRMSE and Logit NRMSE among the evaluated Baseline, DIMC-S-derived, LSAC OR+SXAFA-derived, and Proposed schemes, while the Top-1 accuracy difference relative to the Baseline remained within −0.02%p to +0.12%p.
Edge-AI systems require arithmetic hardware that can support multiple numerical precisions under strict power and resource constraints. This work presents a reconfigurable transprecision SIMD multiply-accumulate (MAC) architecture supporting 1 ×BF16, 2 ×FP8, 4 ×FP4, and 2 ×INT4 operations within a unified framework for...
Shubham Kumar, V. P. Sharma, V. Neema et al.· International Symposium on V...· 0 citations
Posit arithmetic offers a compelling alternative to the IEEE 754 floating-point standard, providing enhanced accuracy. Its fused multiply-accumulate operations avoid intermediate rounding, ensuring exact numerical reproducibility through the quire, a wide fixed-point accumulator spanning the format's full dynamic range...
Mario Alonso, Miguel A. Sacristán, G. Botella et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.