This inventor holds 1 USPTO granted patent. Top assignee: Stmicroelectronics Pvt. Ltd.. Active years: 2011.
Company Filing History:
Years Active: 2011
Title: Srijib Narayan: Innovator in Multi-Processor FFT/IFFT Systems
Introduction
Srijib Narayan is a notable inventor based in West Bengal, India. He has made significant contributions to the field of multiprocessor architectures, particularly in the area of Fast Fourier Transform (FFT) and Inverse Fast Fourier Transform (IFFT) computations. His innovative approach has led to the development of a patented method that enhances computational efficiency.
Latest Patents
Srijib Narayan holds a patent for a "Method and system for multi-processor FFT/IFFT with minimum inter-processor data communication." This invention provides a scalable method for implementing FFT/IFFT computations in multiprocessor architectures. It improves throughput by eliminating the need for inter-processor communication after the computation of the first 'logP' stages, where 'P' represents the number of processing elements. The method involves computing each butterfly of the initial stages on either a single processor or all 'P' processors simultaneously. Subsequent stages are processed by distributing the computation among the 'P' processors, ensuring that each chain of cascaded butterflies is handled by the same processor.
Career Highlights
Srijib Narayan is currently employed at STMicroelectronics Pvt. Ltd., where he continues to work on innovative solutions in the field of electronics and computing. His expertise in multiprocessor systems has positioned him as a valuable asset to his company.
Collaborations
Srijib collaborates with Kaushik Saha, a coworker who shares his passion for advancing technology in their field. Together, they contribute to the development of cutting-edge solutions that address complex computational challenges.
Conclusion
Srijib Narayan's contributions to the field of multiprocessor FFT/IFFT systems exemplify the impact of innovation in technology. His patented method not only enhances computational efficiency but also paves the way for future advancements in multiprocessor architectures.