Sentence examples for multiple compute resources from inspiring English sources

By gathering data streams from multiple compute resources and crunching this data with its state-of-the-art analytics engine, Newvem enables AWS users to discover potential cost savings, identify security vulnerabilities and gain more control over availability.

A parallel computing framework is implemented in the PAPIRUS with multiple computing resources and proper communications between the server and the clients of each processor.

Data parallel pipelining streaming applies when the input of a process is not dependent on any other factors, the particular process is able to be distributed into multiple computing resources and executed in parallel.

In a workflow, it functions well as a glue that connects multiple heterogeneous computing resources, public databases, and private data files to build data analysis pipelines on workstations and computing clusters.

"Our customers efficiently share both storage and compute resources across multiple data centers, and effectively implement and use private and public cloud infrastructures," Bianchini wrote.

Furthermore, the initial multithreaded shared-memory design prevented utilization of resources on multiple compute nodes of a distributed memory cluster.

The design, implementation and optimization of FPGA accelerators is a challenging task, especially when the accelerator comprises multiple compute cores distributed across CPU and FPGA resources and memories and exhibits data-dependent runtime behavior.

While simulation of full-scale catalytic reactors would require domain decomposition based parallelism and use of multiple central processing units, significant performance enhancement can be achieved by fully utilizing the compute resources available within each node in emerging architectures.

Scientific problems that depend on processing large amounts of data require overcoming challenges in multiple areas: managing large-scale data distribution, controlling co-placement and scheduling of data with compute resources, and storing, transferring, and managing large volumes of data.

Lower cost of using compute resources.

Lower cost of provisioning compute resources.