AI
Google Rounds Out Insight into TPU Architecture and Inference
This week we have heard much about the inference side of the deep learning workload, with a range of startups emerging at the AI Hardware Summit. …
inference
AI
Facebook Sounds Opening Bell for AI Inference Hardware Makers
Gentlemen (and women), start your inference engines.
One of the world’s largest buyers of systems is entering evaluation mode for deep learning accelerators to speed services based on trained models. …
AI
First Wave of Spiking Neural Network Hardware Hits
Over the last several years we have seen many new hardware architectures emerge for deep learning training but this year, inference will have its turn in the spotlight. …
AI
Xilinx Unveils xDNN FPGA Architecture for AI Inference
FPGAs might not have carved out a niche in the deep learning training space the way some might have expected but the low power, high frequency needs of AI inference fit the curve of reprogrammable hardware quite well. …
AI
A Mythic Approach to Deep Learning Inference
Another Hot Chips conference has ended with yet another deep learning architecture to consider. …
AI
Even at the Edge, Scale is the Real Challenge
Neural networks live on data and rely on computational firepower to help them take in that data, train on it and learn from it. …
AI
Google Research Pushing Neural Networks Out of the Datacenter
Google has been at the bleeding edge of AI hardware development with the arrival of its TPU and other system-scale modifications to make large-scale neural network processing efficient and fast. …
AI
Does Google’s TPU Investment Make Sense Going Forward?
Google created quite a stir when it released architectural details and performance metrics for its homegrown Tensor Processing Unit (TPU) accelerator for machine learning algorithms last week. …
AI
Nvidia Pushes Deep Learning Inference With New Pascal GPUs
No one knows for sure how pervasive deep learning and artificial intelligence are in the aggregate across all of the datacenters in the world, but what we do know is that the use of these techniques is growing and could represent a big chunk of the processing that gets done every millisecond of every day. …