Vignesh Ravi
About Vignesh Ravi
Vignesh Ravi is a Director at Cerebras Systems, specializing in tools development for GPUs to enhance computing performance. He has a strong background in parallel and distributed computing, with extensive experience in deep learning projects and system software development.
Current Role at Cerebras Systems
Vignesh Ravi serves as the Director of Software at Cerebras Systems, a position he has held since 2019. In this role, he engages in tools development for GPUs, focusing on enhancing performance and efficiency in computing tasks. His work contributes to the advancement of large-scale deep learning projects, leveraging his expertise in parallel and distributed computing.
Professional Experience
Vignesh Ravi has a diverse professional background. He worked at Intel Corporation as a GPGPU/Fabric Architect since 2015, contributing to the development of advanced computing technologies. Prior to this, he held several positions, including Senior GPU Engineer at A2Zlogix for nine months in 2014 and Senior Member of Technical Staff at AMD for three months in the same year. His earlier roles include Graduate Research Associate and Graduate Teaching Associate at The Ohio State University, where he was involved in research and education.
Education and Expertise
Vignesh Ravi earned his Doctor of Philosophy (Ph.D.) in Computer Science and Engineering from The Ohio State University, where he studied from 2007 to 2012. He also holds a Bachelor's degree in Computer Science and Engineering from PSG College of Technology, completed in 2005. His academic background supports his expertise in developing system software and runtimes for CPU-GPU architectures, as well as his interest in emerging programming models like Map-Reduce.
Background in Computing
Vignesh Ravi has a strong foundation in computing, with a focus on parallel and distributed computing. His professional interests include energy-efficient computing solutions and cloud computing. He has engaged in various projects that leverage his skills in GPU performance enhancement and system software development, contributing to advancements in the field.