Graph processing is widely used in cloud services; however, current frameworks face challenges in efficiency and cost-effectiveness when deployed under the Infrastructure-as-a-Service model due to its limited elasticity. In this paper, we present ...

GPUs are essential for accelerating Machine Learning (ML) workloads. A common practice is deploying ML jobs as containers managed by an orchestrator such as Kubernetes. Kubernetes schedules GPU workloads by exclusively assigning a device to a single job, ...

In multi-container environments, applications oftentimes experience unexpected performance fluctuations due to undesirable interference among applications. Synchronization such as locks has been targeted as one of the reasons but still remains an ...

In areas such as manufacturing or logistics, it is beneficial for everyone to share access capacity with others. Increased efficiency increases profits, lowers prices for consumers, and reduces environmental impact. However, in order to share a resource ...

To achieve resource-efficient hardware designs, high-level synthesis (HLS) tools share (i.e., time-multiplex) functional units among operations of the same type. This optimization is typically performed in conjunction with operation scheduling to ensure ...

Online social networks are now common place in day-to-day lives. They are also increasingly used to drive social action initiatives, either led by government or communities themselves. However, such initiatives are mainly used for crowd sourcing ...

Problem definition: Patient-level data from 72 magnetic resonance imaging (MRI) hospitals in Ontario, Canada from 2013 to 2017 show that over 60% of patients exceeded their wait time targets. We conduct a data-driven analysis to quantify the reduction in ...

To improve the performance while reducing the power consumption, embedded processors in Systems-on-Chip (SoC) often now include tightly coupled hardware accelerators that can execute dedicated tasks orders of magnitude more efficiently (faster and lower ...

Attribute-based Access Control (ABAC), as the name suggests, determines whether an access request be granted based on the attributes or characteristics of the requesting user, those of the requested resource, and the environmental condition in which the ...

High performance computing (HPC), typically used only in research until recently, is being integrated more into undergraduate curricula across disciplines. HPC resources are expensive but lend themselves easily to sharing among institutions. However, in ...

In order to solve the problems of high latency and average routing hops in existing teaching resource sharing methods, a new online assisted teaching resource sharing method based on mobile social networks is proposed. Firstly, combining temporal ...

his paper is based upon a lightning talk given at the NISO Plus conference on February 14, 2023 and it describes interlibrary Loan syste4m, Fulfillment, developed by the Equinox Open Library Initiative. A thriving resource-sharing consortium allows ...

GPU technology has been improving at an expedited pace in terms of size and performance, empowering HPC and AI/ML researchers to advance the scientific discovery process. However, this also leads to inefficient resource usage, as most GPU workloads, ...

The Resource-defined fitness sharing (RFS) algorithm combines resource and fitness sharing techniques to solve exact cover problems. These problems are defined in terms of resources and cooperating species which attempt to solve the problem via co-...

We present a cloud-based ecosystem for urban mobility services that involves citizens, authorities, corporations, resources, and services, all working together towards a common well-being. Our goal is to have a platform that allows the ...

Core-stateless resource sharing solutions implemented in P4 hardware data planes have been proposed in the past few years. They share the idea of tagging packets with special values at the network edge that are then solely used for deciding how to handle ...

Training Deep Learning (DL) model requires multiple resource types, including CPUs, GPUs, storage IO, and network IO. Advancements in DL have produced a wide spectrum of models that have diverse usage patterns on different resource types. Existing DL ...

PDC Place North America is being organised to celebrate and learn from community-based information and resource sharing within urban settings in North America. By organising two hybrid events in Detroit, MI, USA, and Toronto, ON, Canada, we hope to ...

Recent GPU architectures support unified virtual memory (UVM), which offers great opportunities to solve larger problems by memory oversubscription. Although some studies are concerned over the performance degradation under UVM oversubscription, the ...

To meet the massive and emergent logistics demand, learning from Europe and the USA, a cooperation mechanism can form a gathered and scaled logistics park network. Based on the current practice in China, the logistics Cloud platform makes the cooperation ...