This month EURA NOVA has presented the paper “A Distributed Data Mining Framework Accelerated with Graphics Processing Units” at the 2013 CloudCom-ASIA conference in Fuzhou, China. This is the third time that EURA NOVA has published a paper in this conference which is now considered one of the three most important IEEE event covering the topic of Cloud Computing.
With the holiday season approaching, brands are releasing the product that they want us to buy to our relatives (or to ourselves).
In the context of processing high volumes of data, the recent developments have led to numerous models and frameworks of distributed processing running on clusters of commodity hardware. On the other side, the Graphics Processing Unit (GPU) has seen much enthusiastic development as a device for general-purpose intensive parallel computation. In this paper we propose a framework which combines both approaches and evaluates the relevance of having nodes in a distributed processing cluster that make use of GPU units for further fine-grained parallel processing. We have engineered parallel and distributed versions of two data mining problems, the naive Bayes classifier and the k-means clustering algorithm, to run on the framework and have evaluated the performance gain. Finally, we also discuss the requirements and perspectives of integrating GPUs in a distributed processing cluster, introducing a fully distributed heterogeneous computing cluster.
Nam-Luc Tran, Quentin Dugauthier, and Sabri Skhiri, A Distributed Data Mining Framework Accelerated with Graphics Processing Units, proceedings of the 2013 International Conference on Cloud Computing and Big Data (CloudCom-Asia), FuZhou, China, December 2013.
Last week Cyrille & François have had the chance to attend the “TechCrunch Disrupt Europe 2013” event in Berlin. This event main topic was the booming new technological and venture opportunities that are materializing for european startups. EURA NOVA’s objectives were to take a look at the “big European picture” and exchange knowledge with brilliant entrepreneurs from all around the world.
Cyrille & François came back boosted by a lot of inspiring stories summarized in this discussion. Enjoy!
Last month Nokia Devices and Services were bought by Microsoft.
Before letting Microsoft build their own Lumia and Asha devices, Nokia still had to release their latest products:
These past years the Graphics Processing Units have gained popularity and momentum in industrial research thanks to the parallel processing power (# of parallel core) that these offers for a reasonable price. The second reason behind this is their wide hardware availability in the consumer landscape: the sheer price cost of a GPU has favored their presence in most of the consumer devices nowadays, from mobile phones & tablets to video game systems.
IS THE FUTURE OF BUSINESS TOTALLY HUMAN CENTRIC?
Today, we see a lot of young developers and designers that grew up with technologies, new social habits and a lot of new tools that did not exist for the previous generation (actually, a generation is no more than 10 years today!).
As a consequence, entrepreneurs in their early 20’s are creating and innovating using technical stacks they have known their whole life, unaware of the details of a CPU, who Turing was and what a methodology can bring to a development project. They just create and diffuse their ideas!
… and people consume their products, get new habits and change their way of viewing/judging things.
This week I was the second IEEE Big Data conference at Santa Clara for presenting our paper “A distributed approach for graph-oriented multidimensional analysis”.
This is now a tradition, I cannot attend a conference without giving you a short summary of the trends and interesting topics of the conference.
In this blog post we briefly describe our new contribution to the big data domain, especially, graphDB benchmarking. This work was accepted for publication at 2013 ASE/IEEE International Conference on Big Data.
In this work, we presented a distributed graph database benchmarking framework. We used this tool to analyze the performance of four graph databases: Neo4j 1.9M05 , Titan 0.3, OrientDB 1.3 and DEX 4.7.
First let’s take a sneak peek at the smartphone market: