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We present direct performance measurement for eight popular HPC applications on the Knights Landing (KNL) platform. Performance numbers for Haswell processors are provided for contrast. The applications (DGEMM. SGEMM, STREAM, IOR, HPCG, Quantum Espresso, WRF and HPL) were selected from among the ten most used in the QCT developer cloud as well as good representative of workloads used by large number...
We present the direct performance measurements of two popular weather forecast models, Weather Research and Forecast Model (WRF) and Models for Predictions Across Scales (MPAS) on Intel's Knight Landing Platform (KNL). WRF is widely evaluated over different platforms while the benchmarks of MPAS are still scarce. In this study we measured the running time of WRF and MPAS on the QCT Developer Cloud,...
Storage demands in the data centers are growing dramatically for most internet and cloud service providers today. More and more service providers are adopting Software-Defined Storage (SDS) instead of traditional fiber channel based storage appliances due to the lead time, expense, and flexibility. However, data centers are held back by storage I/O that cannot keep up with ever-increasing demand,...
Cloud computing and big data technologies are converging to offer a cost-effective delivery model for cloud-based big data analytics. Though impacts of size and scaling of big data on cloud have been extensively studied, the effects of complexity of underlying analytic methods on cloud performance have received less attention. This paper will develop and evaluate a computationally intensive statistical...
We present direct performance measurements for four popular scientific simulations on the Knights Landing (KNL) platform. Performance numbers for Broadwell processors are provided for contrast. The applications (NAMD, LAMMPS, GROMACS and CP2K) were selected from among the ten most used in the QCT developer cloud as well as best representative of workloads used by many users and, given their diversity,...
OpenHPC is a collaborative project conducted by Linux Foundation to lower barriers to deployment, management, and use of modern HPC system with reference collection of open-source HPC software components and best practices. Quanta Cloud Technology (QCT) customized HPC cluster software stack including system provisioning, core HPC services, development tools, and optimized applications and libraries,...
Using genetic data to infer relatedness has been crucial for genetics studies for decades. In a previously published paper together with the KING software, we demonstrated that the kinship coefficient, a measure of relatedness between a pair of individuals, can be accurately estimated using their genome-wide SNP data, without estimating the allele frequencies at each SNP in the whole dataset. The...
Finding the best model to reveal potential relationships of a given set of data is not an easy job and often requires many iterations of trial and errors for model sections, feature selections and parameters tuning. This problem is greatly complicated in the big data era where the I/O bottlenecks significantly slowed down the time needed to finding the best model. In this article, we examine the case...
Deep learning is a sub-set of machine learning practice employing models based on various learning network architectures and algorithms in the field of artificial intelligence. Businesses planning to adopt a deep learning solution should comprehend a set of complex choices in hardware, software, configuration and optimizations to setup a functional deep learning solution. This paper will describe...
In recent years, there are many scheduling algorithms for execution of workflow applications using Quality of Service (QoS) parameters. In this paper, we improve a scheduling workflow algorithm considering the time and cost constraints on heterogeneous resources, which is called Budget-Deadline constrained using Sub-Deadline scheduling (BDSD). With the deadline and budget constraints required by the...
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