GPU’s are much needed in a cloud environment where processing can be offloaded to GPU leading to performance enhancement in image processing as well as NoSQL deployments.
While everybody requires high compute power it is not every day that we realise that CPU’s can only do a certain part of the work.
GPU’s which were traditionally planned to only influence image processing have changed the way mathematical computing is taking over animation rendering and image processing.
Machine learning, AI and high-performance computing are changing the way companies designed there products.
The capacity to do large computations influence how mathematical problems are being solved. This then resorts to the higher use of mathematical and probabilistic data to solve real-life problems.
Nvidia GPU’s have provided solutions to multiple such problems and with the release to NC V2 V3 series GPU’s the performance goes on increasing.
New VM sizes with Nvidia. Tesla V100 GPU are just accelerating performance a notch higher.
The new ND series with focuses on AI training, deep learning can draw the inference
The ND series is powered by up to 4 Tesla P 40 GPU’s and provide a large GPU memory size up to 24Gb which can help the customers deploy neural net models.
Azure also has NC V2 series which typically target HPC load with up to 4 Nvidia Tesla P 100 GPU’s.
NoSQL application also has similar problems from a performance perspective and applications like couchbase whose N1Q11 was compute intensive could have used performance increase.
OSS NoSQL like Spark has seen increased performance with GPU’s.
