DK Panda from Ohio State University presented this talk at the Stanford HPC & Exascale Conference. “As InfiniBand is getting used in scientific computing environments, there is a big demand to harness its benefits for enterprise environments for handling big data and analytics. This talk will focus on high-performance and scalable designs of Hadoop using native RDMA support of InfiniBand and RoCE.”
Data grid software leader ScaleOut Software is using in-memory computing to achieve operational analytics for real-time decision making. There are real benefits in support of in-memory technology when it comes to fraud alerts, transportation management, and taking advantage of short-lived financial opportunities.
One of the unwritten axioms of data scientists specializing in machine learning methodologies is that they all try their hand at predicting the stock market. Some of the best attempts have turned a tidy profit, still others have seen their way into the top hedge fund companies.
“Big data techniques offer a way to analyze data pooled across many patients: their specific disease mutations, biological markers, the treatments, and outcomes — in order to identify unexpected ways that existing therapies can be applied and combined to create personalized treatments that dramatically improve the chances of survival.”
“Map-D uses multiple NVIDIA GPUs to interactively query and visualize big data in real-time. Map-D is an SQL-enabled column store that generates 70-400X speedups over other in-memory databases. This talk discusses the basic architecture of the system, the advantages and challenges of running queries on the GPU, and the implications of interactive and real-time big data analysis in the social sciences and beyond.”
“Predictive lead targeting enables you to tap into the social conversations going on among individuals within your targeted companies, including job listings, news and more,” said Leadspace co-founder and VP Products Amnon Mishor. “Based on your Ideal Customer Profile, our automated scoring algorithm identifies the specific organizations that are likely the most open to hearing about your solution, thereby significantly increasing conversions.”
Statistical models that use socio-political data to predict mass atrocities could soon inform governments and NGOs on how and where to take preventative action. The models emerged from one segment of the Tech Challenge for Atrocity Prevention, a competition run by the US Agency for International Development (USAID) and NGO Humanity International.
In this talk, Sean Gourley examines this world of augmented intelligence and shows how our understanding of the human brain is shaping the way we visualize and interact with big data. Gourley argues that the world we are living in is too complex for any single human mind to understand and that we need to team up with machines to make better decisions.