research paper

The rise of deep-learning (DL) has been fuelled by the improvements in accelerators. GPU continues to remain the most widely used accelerator for DL applications. We present a survey of architecture and system-level techniques for optimizing DL applications on GPUs. We review 75+ techniques...

CNNs (convolutional neural networks) have been recently successfully applied for a wide range of cognitive challenges. Given high computational demands of CNNs, custom hardware accelerators are vital for boosting their performance. The high energy-efficiency, computing capabilities and...

Graphics processing unit (GPU), although a powerful performance-booster, also has many security vulnerabilities. Due to these, the GPU can act as a safe-haven for stealthy malware and the weakest ‘link’ in the security ‘chain’. We present a survey of GPU vulnerabilities showed by researchers...