Fast and accurate climate simulations and weather predictions are critic...
Bayesian Optimization Mixed-Precision Neural Architecture Search (BOMP-N...
Neuromorphic computing using biologically inspired Spiking Neural Networ...
Recently, accelerators for extremely quantized deep neural network (DNN)...
Nanopore sequencing generates noisy electrical signals that need to be
c...
Machine learning has recently gained traction as a way to overcome the s...
With the surging popularity of edge computing, the need to efficiently
p...
A key enabler of deploying convolutional neural networks on
resource-con...
Tensor Cores have been an important unit to accelerate Fused Matrix
Mult...
Hybrid storage systems (HSS) use multiple different storage devices to
p...
Ongoing climate change calls for fast and accurate weather and climate
m...
Modern data-intensive applications demand high computation capabilities ...
In literature computer architectures are frequently claimed to be highly...
Ongoing climate change calls for fast and accurate weather and climate
m...
Computation in-memory is a promising non-von Neumann approach aiming at
...
Modern radio telescopes like the Square Kilometer Array (SKA) will need ...
We introduce an Artificial Neural Network (ANN) quantization methodology...
The conventional approach of moving data to the CPU for computation has
...
Near-memory Computing (NMC) promises improved performance for the
applic...
Emerging computing architectures such as near-memory computing (NMC) pro...
While modern convolutional neural networks achieve outstanding accuracy ...