Over the past decade, deep learning networks have revolutionized the task of classification and recognition in a broad area of applications. Recent developments have shown how these workloads can be implemented on low-power, Arm-based platforms.
During this webinar, you will gain an insight into:
• The recently introduced class of algorithms that can reduce the arithmetic complexity of convolution layers with small filter sizes
• The latest optimizations techniques for the most common solutions, such as GEMM
• The design of Winograd algorithms, with an analysis of the complexity and the performance achieved for convolutional neural networks