Framework - Convergence of HPC + ML + DL + Analytics

It’s fascinating to be part of an era where a machine (or a cluster of machines) can take on a human & beat it in intelligence. What is remarkable is the ease with which one can find availability of computing and huge amounts of data. Thus finding predictive patterns for machines is becoming much easier. In this apparently revolutionary battle of machinev/sman, enterprises have suddenly un-earthed this wealth of data that has not been effectively used so far. Be it predicting security threats, breakdowns, security breaches, or detecting faults in consumer equipment in advance, it's clear that adapting AI techniques would yield a significant competitive advantage to enterprise solutions. Being aware of this outright benefit, enterprises are fast catching up to these cognitive solutions.

What’s helpful is that Artificial (Machine) intelligence presents us with new possibilities and promotes growth in business by reducing dependency on human which is influenced by emotions, environment and other external and social factors. We help customers to insert human like intelligence into machines to automate repeatable task, Detecting and deterring security threads and fraud, predict user actions and suggest recommendations, process thousands of images and helping to gain insights from them, introduce speech recognition and convert text from audio or audio from text, language translation on the fly, do forecasting by processing historical data, and much more.

We help customers to establish an effective AI strategy into their application with the help of fast computing environment (AI specific infrastructures), AI specific frameworks like TensorFlow, Caffe, CNTK, Platform like Amazon ML, Amazon Sagemaker, Nvidia DGX and NGC, and cloud specific AI services like Amazon Rekognition, Amazon Polly, Amazon Lex and many more to quickly build, train and deploy learning models at scale on cloud or on-premise.

Outcome Driven Engagements
-One-Click workflow Automation of WRF Processing System (WPS), freeing up Adv Admin resources.
- 10x Performance improvement post migration and optimization of GROMACS App from a 8-nodes CPU to 2-nodes GPU Cluster, reduction of Job time from 3509sec to whooping 277sec
- 25% efficiency gain in Optimization of Quantum Espresso (QE), Run time reduction from 24hrs to 18hrs

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