AI
The Shape Of AMD HPC And AI Iron To Come
In the IT business, just like any other business, you have to try to sell what is on the truck, not what is planned to be coming out of the factories in the coming months and years. …
AI
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
Wrenching Efficiency Out of Custom Deep Learning Accelerators
Custom accelerators for neural network training have garnered plenty of attention in the last couple of years, but without significant software footwork, many are still difficult to program and could leave efficiencies on the table. …
AI
Managing Deep Learning Development Complexity
For developers, deep learning systems are becoming more interactive and complex. …
AI
The Golden Grail: Automatic Distributed Hyperparameter Tuning
While it might not be an exciting problem front and center of AI conversations, the issue of efficient hyperparameter tuning for neural network training is a tough one. …
AI
The System Bottleneck Shifts To PCI-Express
No matter what, system architects are always going to have to contend with one – and possibly more – bottlenecks when they design the machines that store and crunch the data that makes the world go around. …
AI
Technology Requirements for Deep and Machine Learning
Having been at the forefront of machine learning since the 1980s when I was a staff scientist in the Theoretical Division at Los Alamos performing basic research on machine learning (and later applying it in many areas including co-founding a machine-learning based drug discovery company), I was lucky enough to participate in the creation and subsequently to observe first-hand the process by which the field of machine-learning grew to become a ‘bandwagon’ that eventually imploded due to misconceptions about the technology and what it could accomplish. …
AI
The Convergence Or Divergence Of HPC And AI Iron
Based on datacenter practices of the past two decades, it is a matter of faith that it is always better to run a large number of applications on a given set of generic infrastructure than it is to have highly tuned machines running specific workloads. …
AI
The Heart Of AMD’s Epyc Comeback Is Infinity Fabric
At AMD’s Epyc launch few weeks ago, Lisa Su, Mark Papermaster, and the rest of the AMD Epyc team hammered home that AMD designed its new Zen processor core for servers first. …
AI
China Tunes Neural Networks for Custom Supercomputer Chip
Supercomputing centers around the world are preparing their next generation architectural approaches for the insertion of AI into scientific workflows. …