October 30, 2024
2:00 PM ET / 1:00 PM CT / 11:00 AM PT / 7:00 PM GMT
Duration: 1 hour
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Summary
When architecting a MOSA (Modular Open Systems Approach) system optimized for GPU AI acceleration in embedded sensor systems, the integration of advanced hardware, software, and middleware is crucial. GPU-powered AI acceleration enables real-time data processing and decision-making, making it ideal for high-demand sensor-based applications. By leveraging modular hardware like high-performance GPGPUs, alongside flexible software and middleware frameworks, system engineers can create a future-proof platform that adapts to evolving AI workloads and mission requirements.
In this webinar, subject matter experts Ken Grob and Chris Fadeley will tackle these challenges and demonstrate AI-based implementations that address the needs of mission requirements while meeting harsh conditions in which these systems are often deployed.
Speakers
Ken Grob
Director, Embedded Technologies
Elma Electronic
Ken Grob is director of embedded technologies for Elma Electronic. He is responsible for driving the company’s integrated platform solutions. He was the co-owner of a well-respected embedded sub-systems integration company. He is a highly respected technical expert in the embedded computing open architectures and a leading contributor to VITA standards and the SOSA™ Technical Standard. Ken holds a BSEE from Drexel University in Philadelphia, PA.
Chris Fadeley
CTO
EIZO Rugged Solutions
Chris Fadeley is the CTO at EIZO Rugged Solutions (ERS) with a strong background in embedded software engineering. He leads all ERS initiatives in AI, Deep Learning, GPGPU processing and optimization. Chris and his team develop unified drivers and APIs that integrate with all of NVIDIA’s software stack and allow interoperability of company’s rugged graphics and video products in most system configurations. He holds a BS Computer Engineering Degree from the University of Florida.
Sponsored by: Elma in partnership with EIZO Rugged Solutions
