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Dedicated Computing Announces Its M1000 AI Edge Acceleration Platform Based on NVIDIA’s IGX Platform

With long-life hardware and software, the M1000 family is ideal for medical device developers augmenting traditional healthcare tools with AI.

Dedicated Computing, a leading original design manufacturer (ODM) of proprietary, embedded computing systems, announced two entries in the M1000 family: the M1300 full-size and M1200 mid-size, high-performance artificial intelligence acceleration platforms. The M1300 features scale to support maximum performance, while the M1200 is optimized for reduced system height to fit into cart-based and boom-mounted use cases.

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The M1000 family is an optimized building block for medical device developers focused on data-driven healthcare applications. System longevity is a key value in the high-performance platform, with a purchase lifecycle of up to ten years and availability to medical device manufacturers. Dedicated Computing’s M1000 platform incorporates a safety microcontroller unit, SmartNIC, and software stack developed and supported by NVIDIA. Runtime layers are included as the primary interface to end user applications.

AI is bringing more features to both medical and industrial devices alike. In healthcare, supporting a clinician’s experience with real-time AI inference has the potential to enhance decisions and improve patient outcomes. The M1000 platform is initially targeted at real-time inference for endoscopy applications. Dedicated’s AI acceleration platform is derived from the NVIDIA IGX platform and is based on NVIDIA IGX Orin to deliver up to 275 AI TOPS and scaling to over 600 AI TOPS with an optional NVIDIA RTX A6000 GPU. The M1000 also features the NVIDIA ConnectX-7, a SmartNIC that delivers up to 200 Gbps networking bandwidth and GPUDirect RDMA, a Magnum IO technology, for ultra-low-latency processing. Combined with the power of the NVIDIA Clara Holoscan SDK, an end-to-end platform for real-time and streaming medical devices that accelerates developers’ workflows, NVIDIA IGX can help deliver secure, low-latency AI inference to meet clinical demands.

Medical device and industrial developers, such as Moon Surgical, are building an entirely new category of robotic surgery, supported by this AI computer and software framework. Such a platform empowers companies to envision and create advanced autonomous systems and AI-powered medical devices that feature superior image, video, and signal processing. They can build global and diverse applications, ranging from endoscopes to advanced surgical displays and more.

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“The NVIDIA IGX platform and the Dedicated Computing M1300, with the NVIDIA Clara Holoscan SDK, together provide the ability to accelerate Moon Surgical’s AI capabilities,” said David Noonan, the CTO at Moon Surgical. “An off-the-shelf hardware and software system solution at this level allows our team to focus on developing novel features and algorithms—saving precious time and capital.”

“It is great to see our product development efforts benefit our customers and their markets in such an impactful way,” said Phil Spivey, CEO at Dedicated Computing. “Our work with NVIDIA on IGX will enhance our customer’s medical devices and equipment with AI at the Edge for many years to come.”

Dedicated Computing’s building-block hardware designs are diverse and proven, keeping the focus on robust data performance and physical durability for the environmental rigors of healthcare and industrial computing. Decades of expertise include applications featuring AI, machine vision, and advanced GPU processing in healthcare applications such as data acquisition for intravascular ultrasound, advanced eye measurements that eliminate subjective processes, lab and cyclotron automation, fluorescence image-guided, and full color 3D image reconstruction based on light instead of radiation. Within the industrial market, example applications powered by Dedicated Computing include quality and safety product inspection, surveillance, and robot/cobot control.

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[To share your insights with us, please write to sghosh@martechseries.com] 

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