JIT compilation, SIMD instructions, GPU computing with CUDA, and FPGAs — the hardware acceleration techniques used in high-performance financial systems.
A new technical paper titled “Hardware Acceleration for Neural Networks: A Comprehensive Survey” was published by researchers at Arizona State University. Abstract “Neural networks have become a dominant computational workload across cloud and edge platforms, but their rapid growth in model size and deployment diversity has exposed hardware bottlenecks that are increasingly dominated by memory...…
Axelera AI, the provider of purpose-built AI hardware acceleration technology for generative AI and computer vision inference at the edge, unveiled Titania, a high-performance, energy efficient and scalable AI inference chiplet. The post Axelera AI Secures up to €61.6 Million Grant to Develop Scalable AI Chiplet for High-Performance Computing appeared first on Semiconductor Digest .
