Compute
MPI on Neuromorphic Hardware Shows Greater Promise
While there are not many neuromorphic hardware makers, those on the market (or in the research device sphere) are still looking for ways to run more mainstream workloads. …
MPI
Code
Rethinking MPI for GPU Accelerated Supercomputers
In the accelerated era of exascale supercomputing, MPI is being pushed to its logical limits. …
Code
The State of MPI for Future Exascale Systems
A working group formed on behalf of the Exascale Computing Project (ECP) in the U.S. …
AI
Taking the Heavy Lifting Out of TensorFlow at Extreme Scale
There is no real middle ground when it comes to TensorFlow use cases. …
AI
Scaling Deep Learning on an 18,000 GPU Supercomputer
It is one thing to scale a neural network on a single GPU or even a single system with four or eight GPUs. …
AI
Pushing MPI into the Deep Learning Training Stack
We have written much about large-scale deep learning implementations over the last couple of years, but one question that is being posed with increasing frequency is how these workloads (training in particular) will scale to many nodes. …
Code
MPI and Scalable Distributed Machine Learning
MPI (Message Passing Interface) is the de facto standard distributed communications framework for scientific and commercial parallel distributed computing. …
Code
Mitigating MPI Message Matching Issues
Since the 1990s, MPI (Message Passing Interface) has been the dominant communications protocol for high-performance scientific and commercial distributed computing. …
Compute
Intel Stretches Deep Learning on Scalable System Framework
The strong interest in deep learning neural networks lies in the ability of neural networks to solve complex pattern recognition tasks – sometimes better than humans. …
Code
A Hybrid Path to Programming Exascale Machines
As we have been describing here in detail, there is little end in sight to the train of exascale computing challenges ahead. …