Imagination Technologies' Upgraded GPUs, New Neural Network Core Provide Deep Learning Processing Options
October 2, 2017
Graphics IP supplier Imagination Technologies has long advocated the acceleration of edge-based deep learning inference operations via the combination of the company's GPU and ISP cores. Latest-generation graphics architectures from the company continue this trend, enhancing performance and reducing memory bandwidth and capacity requirements in entry-level and mainstream SoCs and systems based on them. And, for more demanding deep learning applications, the company has introduced its first neural network coprocessor core family.
To read the full article, click here
Related Semiconductor IP
- GPU
- PowerVR Automotive XS GPU
- E-Series GPU IP
- High performance GPU for cloud gaming with DirectX support
- Arm’s flagship GPU providing ultimate mobile gaming experiences
Related Blogs
- Imagination's neural network accelerator and Visidon's denoising algorithm prove to be perfect partners
- Running LSTM neural networks on an Imagination NNA
- Self-Compressing Neural Networks
- Synopsys Fields Processor Core for Neural Network Computer Vision Applications
Latest Blogs
- World's First Standards-Compliant 112G PHY IP for Linear Optics: A Turning Point for AI Interconnects
- One Key for Every Door: How Aliro Extends the UWB Digital Key Beyond the Car
- Reprogrammable Post-Quantum Security for SoCs: Why Crypto-Agility Matters
- Designing the Beam Steering Core for a C-Band AESA: A Look at VSI's VBF0644 GaAs Beamformer IC
- Secure Boot for embedded systems: Building a complete chain of trust