Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 54 tok/s
Gemini 2.5 Pro 50 tok/s Pro
GPT-5 Medium 18 tok/s Pro
GPT-5 High 31 tok/s Pro
GPT-4o 105 tok/s Pro
Kimi K2 182 tok/s Pro
GPT OSS 120B 466 tok/s Pro
Claude Sonnet 4 40 tok/s Pro
2000 character limit reached

Near-Precise Parameter Approximation for Multiple Multiplications on A Single DSP Block (2104.02162v1)

Published 5 Apr 2021 in cs.AR

Abstract: A multiply-accumulate (MAC) operation is the main computation unit for DSP applications. DSP blocks are one of the efficient solutions to implement MACs in FPGA's. However, since the DSP blocks have wide multiplier and adder blocks, MAC operations using low bit-length parameters lead to an underutilization problem. Hence, an efficient approximation technique is introduced. The technique includes manipulation and approximation of the low bit-length fixed-point parameters based upon a Single DSP - Multiple Multiplication (SDMM) execution. The SDMM changes the traditional MAC implementation in the DSP block by separating multiplication and accumulation operations. While the accumulator hardware available in the DSP block is used for multiple parameter multiplication, parallel LUTs are employed for the accumulation part of the MAC operation. The accuracy of the developed optimization technique was evaluated for different CNN weight bit precisions using the Alexnet and VGG-16 networks and the Tiny ImageNet dataset. The optimization can be implemented without loss of accuracy in almost all cases, while it causes slight accuracy losses in a few cases. Through these optimizations, the SDMM is performed at the cost of a small hardware overhead. For example, a single DSP block executes 3 8-bit fixed-point parameter multiplications. As a result of our optimizations, the parameters are represented in a different format on off-chip memory, providing up to 33% compression without any hardware cost. The compression rate can be further increased by up to 97% when used in conjunction with other compression methods for the VGG-16. Reaching this compression rate requires extra hardware cost. A prototype systolic array architecture was implemented employing our optimizations on a Xilinx Zynq FPGA. It reduced the number of DSP blocks by 66.6%, 75%, and 83.3% for 8, 6, and 4-bit input variables, respectively.

Citations (7)
List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-Up Questions

We haven't generated follow-up questions for this paper yet.