Company Filing History:
Years Active: 2005
Title: Michael W Bartels: Innovator in Fault-Tolerant Computing
Introduction
Michael W Bartels is a notable inventor based in Phoenix, AZ. He has made significant contributions to the field of computing, particularly in developing methods for enhancing data integrity in digital systems. His innovative approach addresses critical challenges in fault tolerance and data recovery.
Latest Patents
Bartels holds a patent for "High integrity recovery from multi-bit data failures." This invention outlines methods and systems designed to facilitate a computing platform's rapid recovery from transient multi-bit data failures within a run-time data memory array. The system operates transparently to software applications executing on the platform. It features a fault-tolerant digital computing system that utilizes parallel processing lanes in a lockstep architecture. Each processing lane is equipped with error detectors that identify multi-bit data errors in their respective memory arrays. Upon detecting a failure, an interrupt is generated, prompting control logic software to respond and correct the data errors in the memory array of each processing lane.
Career Highlights
Bartels is currently employed at Honeywell International Inc., where he continues to innovate and contribute to advancements in computing technology. His work focuses on enhancing the reliability and efficiency of digital systems, making them more resilient to data failures.
Collaborations
Throughout his career, Bartels has collaborated with talented professionals, including Nicholas J Wilt and Scott L Gray. These collaborations have fostered an environment of innovation and have led to the development of cutting-edge technologies in the field.
Conclusion
Michael W Bartels is a distinguished inventor whose work in fault-tolerant computing has made a significant impact on the industry. His patent for high integrity recovery from multi-bit data failures exemplifies his commitment to advancing technology and improving data reliability.