Add to ORKGHow does one cover the needs of both HPC and HPDA (high performance data analytics) applications? Which hardware and software technologies are needed? And how should these technologies be combined so that very different kinds of applications are able to efficiently exploit them? These are the questions that the recently started EU-funded project DEEP-EST addresses with the Modular Supercomputing architecture
High-Performance Big Data Analytics (HPDA) applications are characterized by huge volumes of distrib...
Due to the advancement of the latest-generation remote sensing instruments, a wealth of information ...
Homogeneous cluster architectures, which used to dominate high-performance computing (HPC), are chal...
The results described in this volume have been obtained within the research and development project ...
Accelerators arrived to HPC when the power bill for achieving Flop performance with traditional, hom...
The DEEP-EST Project aims to build a Modular Supercomputer Architecture (MSA) with the main focus on...
Striving at pushing the applications scalability to the limits, the DEEP project proposed an alterna...
The way in which HPC systems are built has changed over the decades. Originally, special purpose com...
High Performance Computing (HPC) centers are the largest facilities available for science. They are ...
The user requirements imposed by modern challenges are influencing future High Performance Computing...
The Big Data era poses a critically difficult challenge and striking development opportunities in Hi...
We observe a continuously increased use of Deep Learning (DL) as a specific type of Machine Learning...
At the present time, we are immersed in the convergence between Big Data, High-Performance Computing...
International audienceData-intensive computing and HPC are two different computing paradigms (data-c...
Homogeneous cluster architectures dominating high-performance computing (HPC) today are challenged, ...
High-Performance Big Data Analytics (HPDA) applications are characterized by huge volumes of distrib...
Due to the advancement of the latest-generation remote sensing instruments, a wealth of information ...
Homogeneous cluster architectures, which used to dominate high-performance computing (HPC), are chal...
The results described in this volume have been obtained within the research and development project ...
Accelerators arrived to HPC when the power bill for achieving Flop performance with traditional, hom...
The DEEP-EST Project aims to build a Modular Supercomputer Architecture (MSA) with the main focus on...
Striving at pushing the applications scalability to the limits, the DEEP project proposed an alterna...
The way in which HPC systems are built has changed over the decades. Originally, special purpose com...
High Performance Computing (HPC) centers are the largest facilities available for science. They are ...
The user requirements imposed by modern challenges are influencing future High Performance Computing...
The Big Data era poses a critically difficult challenge and striking development opportunities in Hi...
We observe a continuously increased use of Deep Learning (DL) as a specific type of Machine Learning...
At the present time, we are immersed in the convergence between Big Data, High-Performance Computing...
International audienceData-intensive computing and HPC are two different computing paradigms (data-c...
Homogeneous cluster architectures dominating high-performance computing (HPC) today are challenged, ...
High-Performance Big Data Analytics (HPDA) applications are characterized by huge volumes of distrib...
Due to the advancement of the latest-generation remote sensing instruments, a wealth of information ...
Homogeneous cluster architectures, which used to dominate high-performance computing (HPC), are chal...