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[Webcast] Heterogenous Computing: Effective Use of CPUs and GPUs in Embedded Systems Design

 

The advancement in IoT technology and AI applications is driving the demand for even more processing power. CPU alone is no longer sufficient to process advanced AI algorithms in a timely manner. This is where GPUs come into play. CPUs offload certain tasks to GPUs, which use parallel computing to utilize thousands of cores to optimize these advanced intelligent applications.  

Watch the webcast on-demand and learn about the roles of CPUs and GPUs in embedded systems and advanced edge applications with Sean Chen, Solution Engineer here at Premio Inc.

 

 

What is Rugged Edge Computing? 

Garner estimates 75% of data will be processed outside of the cloud by 2025. Edge computing reduces latency and frees up bandwidth by bringing data aggregation, processing, and storage closer to the source of data. This enables massive amounts of real-time computation to deliver data insights to facilitate faster and more accurate decisions and actions. To achieve this, a holistic hardware strategy is fundamental. Download the free Rugged Edge Survival Guide eBook to learn more about hardware requirements for a successful edge computing deployment.  

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Hardware Acceleration for AI Applications at the Edge 

 

 

The convergence of Artificial Intelligence, 5G connectivity, and edge computing accelerates digital transformation and creates new opportunities across business sectors. Adopting AI-powered applications becomes imperial to stay competitive. Hardware accelerations are often deployed to optimize performance for advanced AI, machine learning, and deep learning applications. Follow the link to learn more about dedicated hardware accelerators for AI workloads at the edge.  

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Data Insights From The Cloud And Out To The Edge  

DPUs are data processing units that are specifically designed to accelerate and optimize networking, storage, and security functions. In fact, DPUs can free up 30% to 50% utilization from host CPU. This allows CPUs to focus on critical general-purpose applications to increase overall efficiency. 

The FlacheStreams DPU accelerated rackmount server is designed to provide high-performance results that enable new architectures from the latest technologies in CPUs, GPUs, and DPUs. This purpose-built server addresses the most complex data center workloads in today’s modern-day infrastructures for public, private, and hybrid cloud models that require a balance of incredible hardware acceleration. 

Learn More About DPU Accelerated Servers >> 

AI Edge Inference Computers 

Premio’s 5G ready RCO-6000-CFL Series are purpose-built for AI inference applications at the edge with advanced technologies such as Intel 9th Generation Core Processors, GPU support, and hot-swappable NVMe SSD storage.  

The RCO-6000-CFL series is built with flexibility and scalability in mind. Thetwo-piecemodular design provides variations in NVMe SSDs storage and GPUs acceleration configuration options to address specific application requirements. This flexible modularity allows system integrators to quickly deploythe RCO-6000-CFL AI Edge Inference computer in scale even with various application requirements in compute, storage, and connectivity.