MOREH, THE DAY AFTER TOMORROW
THE ENABLER OF FUTURE AI ACCELERATORS
MOREH
About Us
Moreh is an AI start up focusing on maximizing the scalability of the AI market. Founded in 2020, we believe that easier access to AI infrastructure is necessary to the expansion of the entire AI industry. In order to achieve our vision, we are dedicated to solve the current constraints of datacenters by providing an AI infrastructure solution that guarantees scalability and flexibility. Moreh's global team are comprised of industry leading architects and engineers with comprehensive capabilities for AI infrastructure. We are confident in expanding AI accelerator market to reach its full potential and believe that our contribution will change the course of the market.
Technology
Moreh AI Platform for AI Accelerator
World's most compatible and flexible AI Infrastructure Software
Moreh AI Platform is a software stack for tomorrow’s AI models and infrastructures. Moreh AI Platform enables users to accelerate AI applications seamlessly on a variety of processors and on a diverse system scales, from single chips to large clusters, with the help of our compiler technology. Customers can focus on important AI problems regardless of complicated hardware architecture and parallelization techniques. By eleminating proprietary components from our software stack, AI systems can be built in a cost-effective way without being tied to a specific hardware vendor. We provide full compatibility with standard deep learning frameworks including PyTorch and TensorFlow. The rapidly expanding AI software ecosystem can be powered by our platform without any code modification.
Leadership
Doyeon Yun
Doyeon Yun is CEO of Moreh. He is a business and techincal professional with broad skill set who is committed to growing the business, combined with in-depth knowledge of the issues between AI technology and service providers. He was a VP of Business Development at FADU, a successful fabless semiconder innovator. He is a former consultant at Bain & Company and was involved in multiple projects in tech industry such as semiconductor and AI/cloud software. He holds a B.A. in Business Administration from Seoul National University.
Jungho Park
Jungho Park is CTO of Moreh. He received his PhD degree in Electrical Engineering and Computer Science from Seoul National University, where he studied GPU-accelerated computing for more than 10 years. Before joining the team, he co-founded ManyCoreSoft, a startup that provides comprehensive high-performance computing solutions for AI, finance, and medical applications. He has a BS in Computer Science and Engineering from Seoul National University.
Gangwon Jo
Gangwon Jo is Chief Architect of Moreh. He received a PhD in Electrical Engineering and Computer Science and a BS in Computer Science and Engineering both from Seoul National University. During his studies at SNU, he focused on developing compilers and runtime systems for accelerators, which become the basis of the Moreh solution.
Jaejin Lee
Jaejin Lee is advisor and co-founder of Moreh. He is also a professor in the Dept. of Computer Science & Engineering and Dept. of Data Science at Seoul National University. He leads the Thunder Research Group at SNU, the birthplace of remarkable heterogeneous supercomputers and their software. He received his PhD degree in Computer Science from the University of Illinois at Urbana-Champaign, an MS degree in Computer Science from Stanford University, and a BS degree in Physics from Seoul National University. He is an IEEE fellow.
Join our Team
Be part of Moreh, be part of future
Be part of a fast growing, passionate, fearless, innovative team looking beyond tomorrow's AI world
Be part of a global team to solve the most critical challenges in AI industry.
Don't be part of Today, don't be part of Tomorrow, be part of Moreh
C++ 프로그래머
클라우드 환경에서 NVIDIA GPU 외의 다양한 가속기 프로세서를 사용할 수 있도록 하는 PyTorch / TensorFlow 호환 딥 러닝 Framework 개발
AI 응용 개발자
최신 인공지능 연구 동향을 지속적으로 파악하고, 새로운 딥 러닝 모델을 학습시키기 위한 PyTorch, TensorFlow 프로그램을 조사, 구현, 분석하여 Moreh Framework 위에서 테스트 진행
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