Smaller clusters often overload a single server with multiple services such as file, resource scheduling, plus monitoring/management. While this approach may work for systems with fewer than 100 nodes, these services can overload the cluster network or the single server as the cluster grows. InsideHPC Guide show a plan for scalable HPC cluster growth
“We need to educate new legions of students in high-performance computing,” said James Lin, vice director Center for HPC at SJTU. “Teaching HPC skills in a competition like this can be more effective than in a classroom. In fact, as a result of his experience, one of our team members decided to focus on an HPC PhD at Virginia Tech.”
“This talk will focus on challenges in designing software libraries and middleware for upcoming exascale systems with millions of processors and accelerators. Two kinds of application domains – Scientific Computing and Big data will be considered. For scientific computing domain, we will discuss about challenges in designing runtime environments for MPI and PGAS (UPC and OpenSHMEM) programming models by taking into account support for multi-core, high-performance networks, GPGPUs and Intel MIC. “
Today Cray announced that the Center for Computational Sciences (CCS) at the University of Tsukuba in Japan has installed their second Petascale Cray CS300 supercomputer.
The basic HPC cluster consists of at least one management/login node connected to a network of many worker nodes. Depending on the size of the cluster, there may be multiple management nodes used to run cluster-wide services, such as monitoring, workflow, and storage services. This insideHPC article series looks at the Five Essential Strategies for Managing HPC Clusters.
“When OpenACC first appeared it made sense to use this forum to experiment with new approaches while the use of GPUs in HPC was evolving rapidly, with the expectation that the best ideas would then be reintroduced into OpenMP. But OpenMP and OpenACC now seem to be diverging. Indeed, a comparison of OpenACC and OpenMP on the OpenACC web site says “efforts so far to include support for GPUs in the OpenMP specification are — in the opinions of many involved — at best insufficient, and at worst misguided.”
“We need to emphasize here that the Knights Landing processor is self-hosted, and so that means it’s not an accelerator. It’s not a coprocessor and the particular kernel processor that will be having for NERSC-8, will have more than 60 cores and it will have multiple hardware threads for the core. That’s a lot, right? Having 60 cores per node with multiple hardware thread. That a significant increase from both our Hopper and Edison system, which has 24 cores each. So we’re going to be working with our users to figure out what’s the right amount of parallelism that they need to expose in their application. That’s one really big difference.”