Deep Learning Acceleration Platforms Deliver the Optimal Mix of SWaP and AI Performance
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Demand is intensifying for image rendering, image analysis, compute acceleration, and artificial intelligence (AI) in many embedded market segments. Solution providers should consider Edge AI, which can respond faster than cloud AI by eliminating the need to send large data volumes to the cloud. To power compute-hungry applications, ADLINK heterogeneous systems combine graphics processing units (GPUs) and CPUs to achieve the right mix of size, weight, and power (SWaP) and AI performance. Download the application note to learn how the ADLINK DLAP Series reduces development cost and time-to-market for industrial-grade applications.
- Challenges for AI applications at the edge
- Importance of heterogeneous computing for AI
- System SKUs to optimize SWaP and performance
- Customization and deep learning consultancy services
keyword: MXM, GPU, DLAP, Turing, Deep Learning, AI, inference, RTX, Quadro, NVIDIA, edge AI, edge computing