相关论文: An Elastic Job Scheduler for HPC Applications on t…

Cloud resource management is often modeled by two-dimensional bin packing with a set of items that correspond to tasks having fixed CPU and memory requirements. However, applications running in clouds are much more flexible: modern…

Overdecomposition has emerged as a powerful and sometimes essential technique in parallel programming. Many application domains or frameworks, including those based on adaptive mesh refinements, or tree codes use it. Charm++ is a parallel…

Cloud computing technology has been one of the most critical developments in provisioning both hardware and software infrastructure in recent years. Container technology is a new cloud technology that boosts the booting of applications,…

Businesses have made increasing adoption and incorporation of cloud technology into internal processes in the last decade. The cloud-based deployment provides on-demand availability without active management. More recently, the concept of…

HPC systems keep growing in size to meet the ever-increasing demand for performance and computational resources. Apart from increased performance, large scale systems face two challenges that hinder further growth: energy efficiency and…

The technologies of heterogeneous multi-core architectures, co-location, and virtualization can be used to reduce server power consumption and improve system utilization, which are three important technologies for data centers. This article…

Open-source matters, not just to the current cohort of HPC users but also to potential new HPC communities, such as machine learning, themselves often rooted in open-source. Many of these potential new workloads are, by their very nature,…

In Covid-19 pandemic, the number of users connecting to the Internet using mobile devices increased. People are doing there every task using mobile phones [16]. These devices are battery-powered and have limited computation capabilities.…

In recent years, serverless computing, especially Function as a Service (FaaS), is rapidly growing in popularity as a cloud programming model. The serverless computing model provides an intuitive interface for developing cloud-based…

In Mobile Edge Computing (MEC), Internet of Things (IoT) devices offload computationally-intensive tasks to edge nodes, where they are executed within containers, reducing the reliance on centralized cloud infrastructure. Frequent upgrades…

Dynamic resource management is an increasingly important capability of High Performance Computing systems, as it enables jobs to adjust their resource allocation at runtime. This capability can reduce workload makespan, substantially…

Production-quality parallel applications are often a mixture of diverse operations, such as computation- and communication-intensive, regular and irregular, tightly coupled and loosely linked operations. In conventional construction of…

Balancing the workload of sophisticated simulations is inherently difficult, since we have to balance both computational workload and memory footprint over meshes that can change any time or yield unpredictable cost per mesh entity, while…

HPC users aim to improve their execution times without particular regard for increasing system utilization. On the contrary, HPC operators favor increasing the number of executed applications per time unit and increasing system utilization.…

Scientific communities are increasingly using geographically distributed computing platforms. The current methods of compute placement predominantly use logically centralized controllers such as Kubernetes (K8s) to match tasks to available…

Industries are considering the adoption of cloud computing for real-time applications due to current improvements in network latencies and the advent of Fog and Edge computing. To create an RT-cloud capable of hosting real-time…

MPI applications begin with a fixed number of rank and, by default, the rank remains constant throughout the application's lifetime. The developer can choose to increase the rank by dynamically spawning MPI processes. However doing this…

Work-stealing is a widely used technique for balancing irregular parallel workloads, and most modern runtime systems adopt lock-free work-stealing deques to reduce contention and improve scalability. However, existing algorithms are…

For distributed applications to take full advantage of cloud computing systems, we need middleware systems that allow developers to build elasticity management components right into the applications. This paper describes the design and…

The soaring energy demands of large-scale software ecosystems and cloud data centers, accelerated by the intensive training and deployment of large language models, have driven energy consumption and carbon footprint to unprecedented…