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Barcelona, Novermber 4th 2015 -- Made of Genes selects the proposal submitted by HPCNow! for the implementation, setup and maintenance of an HPC solution.

Made of Genes was founded with the mission to create the necessary framework for anyone to have a monitored and informed access to their genome by adopting genomic analysis techniques in prevention, diagnosis and personalized treatments. Made of Genes has the ultimate aim of improving the welfare and quality of life of the society. The technology infrastructure proposed by HPCNow! will allow the company to continue carrying out tasks such as interpreting and analyzing genomic data, secure data management, integrating software for analysis or collaborating in research projects.

The project has been designed with the aim of providing a high-performance scientific computing, high density, efficient, environmentally friendly, easy to manage and scalable system. Regarding the hardware, the offer is based on high density ASUS servers that host the management, backup and computing nodes. Both the management and backup nodes are equipped with 32GB of memory, two 6 core, 1.6GHz processors and 3 SATA discs; while the computing nodes are provided by 64GB of memory, two 8 core, 2.4GHz processors and two SATA disks.

The software installed on the management node is a distribution of the sNow! suite, developed by the HPCNow! team and specifically designed to manage clusters in scientific computing environments. The purpose of sNow! is to provide scientists and engineers with an easy to use and manage system, avoiding the complexities that come with the management of computer clusters. sNow! incorporates a set of virtual machines that host services like the batch system Slurm and monitoring applications such as Icinga and Ganglia.

Finally, the HPCNow! team was in charge of the installation of the sNow! suite in the management node, the configuration of services and the installation of the most used scientific applications by Made of Genes in the computing nodes in order to achieve the best performance out of the solution.




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