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Sreehari Veeramachaneni

Publications and source records attributed to Sreehari Veeramachaneni.

2 recordsLinked to original sources

An Energy-Efficient Approximate Posit Multiply-Divide Unit

In modern computing units, division operations are generally slower than other arithmetic operations and require more resources, such as area and power, than multiplication. To reduce the delay, fast division algorithms use an initial approximation of the reciprocal of the divisor and iteratively approach the correct value, followed by multiplication with the dividend. The hardware architecture and choice of algorithm can significantly alter the overall performance of the division unit. This paper proposes a reduced-accuracy division method for the posit number system, which is an alternative to the traditional floating-point system. The proposed design uses a Look-Up Table (LUT) and a single subtraction operation to perform approximate divisor reciprocation by leveragingthemathematicalsymmetriesofthepositnumbersystem.The paper also presents a hardware architecture that combines multiplication and division units. The reciprocal calculation has been incorporated into the posit Decoder, a common unit required to perform any hardware operation with posits. Compared to existing hardware implementations of division, the proposed method requires significantly fewer operations at the cost of perfect rounding for division. The proposed architecture was simulated using the Cadence RTL v7.1 E2 compiler at the TSMC 90 nm process node and achieves a Power Delay Product (PDP) reduction of 78.8% compared to an existing design that performs exact division, while only 46.33% of the area is required. The experimental results also demonstrate the effectiveness of the proposed system in improving the efficiency of multiplication in posit-based systems.

cs.AR↗

Approximate Signed Multiplier with Sign-Focused Compressor for Edge Detection Applications

This paper presents an approximate signed multiplier architecture that incorporates a sign-focused compressor, specifically designed for edge detection applications in machine learning and signal processing. The multiplier incorporates two types of sign-focused compressors: A + B + C + 1 and A + B + C + D + 1. Both exact and approximate compressor designs are utilized, with a focus on efficiently handling constant value "1" and negative partial products, which frequently appear in the partial product matrices of signed multipliers. To further enhance efficiency, the lower N - 1 columns of the partial product matrix are truncated, followed by an error compensation mechanism. Experimental results show that the proposed 8-bit approximate multiplier achieves a 29.21% reduction in power delay product (PDP) and a 14.39% reduction in power compared to the best of existing multipliers. The proposed multiplier is integrated into a custom convolution layer and performs edge detection, demonstrating its practical utility in real-world applications.

cs.AR↗