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Scalable system scheduling for HPC and big data
In the rapidly expanding field of parallel processing, job schedulers are the “operating
systems” of modern big data architectures and supercomputing systems. Job schedulers …
systems” of modern big data architectures and supercomputing systems. Job schedulers …
Towards HPC and big data analytics convergence: Design and experimental evaluation of a HPDA framework for escience at scale
D Elia, S Fiore, G Aloisio - IEEE Access, 2021 - ieeexplore.ieee.org
Over the last two decades, scientific discovery has increasingly been driven by the large
availability of data from a multitude of sources, including high-resolution simulations …
availability of data from a multitude of sources, including high-resolution simulations …
Scheduler technologies in support of high performance data analysis
Job schedulers are a key component of scalable computing infrastructures. They orchestrate
all of the work executed on the computing infrastructure and directly impact the effectiveness …
all of the work executed on the computing infrastructure and directly impact the effectiveness …
Teaching and learning HPC through serious games
Serious games provide pathways for learners to develop intuition about concepts that are
new to them. Such games are especially valuable in an educational context because they …
new to them. Such games are especially valuable in an educational context because they …
Node-based job scheduling for large scale simulations of short running jobs
Diverse workloads such as interactive supercomputing, big data analysis, and large-scale AI
algorithm development, requires a high-performance scheduler. This paper presents a novel …
algorithm development, requires a high-performance scheduler. This paper presents a novel …
Dbos: A proposal for a data-centric operating system
Current operating systems are complex systems that were designed before today's
computing environments. This makes it difficult for them to meet the scalability …
computing environments. This makes it difficult for them to meet the scalability …
Hyperscaling internet graph analysis with d4m on the mit supercloud
Detecting anomalous behavior in network traffic is a major challenge due to the volume and
velocity of network traffic. For example, a 10 Gigabit Ethernet connection can generate over …
velocity of network traffic. For example, a 10 Gigabit Ethernet connection can generate over …
Benchmarking data analysis and machine learning applications on the Intel KNL many-core processor
Knights Landing (KNL) is the code name for the second-generation Intel Xeon Phi product
family. KNL has generated significant interest in the data analysis and machine learning …
family. KNL has generated significant interest in the data analysis and machine learning …
Processing of crowdsourced observations of aircraft in a high performance computing environment
As unmanned aircraft systems (UASs) continue to integrate into the US National Airspace
System (NAS), there is a need to quantify the risk of airborne collisions between unmanned …
System (NAS), there is a need to quantify the risk of airborne collisions between unmanned …
Benchmarking the processing of aircraft tracks with triples mode and self-scheduling
As unmanned aircraft systems (UASs) continue to integrate into the US National Airspace
System (NAS), there is a need to quantify the risk of airborne collisions between unmanned …
System (NAS), there is a need to quantify the risk of airborne collisions between unmanned …