NVIDIA CUDA® 核心以 GPU 加速能力支援通用運算。凌華科技的 GPU 解決方案搭配 Tensor Core，加快了人工智慧推論與訓練速度，另外使用 RT Core，採用即時光線追蹤技術，提高渲染出電影般影像的效能和速度，以更快速度呈現出更優秀的結果。
凌華科技的 MXM GPU 模組只有 PCIe 繪圖卡的五分之一大小，讓搭載的主機系統可以微型化。該模組能夠承受工業環境中惡劣的實際挑戰，包括震動、衝擊與極端溫度。凌華科技的 MXM GPU 模組也擁有出色的節能表現，最低功耗僅只有 20 瓦。
There is a growing need for GPUs at the edge. Compared with traditional graphics cards, ADLINK embedded MXM graphics cards offer similar performance, but is more power-efficient and only one-fifth the size. Also, they can survive severe temperature extremes, shock and vibration. ADLINK embedded MXM graphics cards can deliver AI inference and compute acceleration to size, weight and power constrained edge applications.
The need for computing is growing exponentially at the edge. The market size is expected to reach USD 155.9 billion by 2030, expanding at a CAGR of 38.9%*. Leveraging the power of GPUs enables industries to better position for edge computing. Download the infographic to learn seven ways to facilitate the edge transition with embedded MXM GPU modules.
Bringing AI to the edge provides many benefits, including faster response time, enhanced security, improved mobility, and lower communication costs. As combinations of neural networks and frameworks, running on specialized computing cores, are ideal for specific tasks, heterogeneous computing is the best strategy for deploying AI. Download the solution brief to learn how to optimize an AI platform with CPU, GPU, FPGA, and ASIC.