The efficiency of distributed shared memory (DSM) has been greatly improved by recent hardware technologies. But, the difficulty of distributed memory management can still be a major obstacle to the democratization of DSM, especially when a partial ...

Virtual and Augmented Reality is one of the key driving technologies of the 4th Industrial Revolution, which is expected to radically disrupt almost every business sector and transform the way we live and interact with our environment and each other. ...

We present GiantVM,¹ an open-source distributed hypervisor that provides the many-to-one virtualization to aggregate resources from multiple physical machines. We propose techniques to enable distributed CPU and I/O virtualization and distributed shared ...

Distributed shared memory abstraction can coordinate a cluster of machine nodes to empower performance-critical queries with the scalable memory space and abundant parallelism. But to deploy the query under such an abstraction, the general execution ...

The large diffusion of multi-core machines has pushed the research in the field of Parallel Discrete Event Simulation (PDES) toward new programming paradigms, based on the exploitation of shared memory. On the opposite side, the advent of Cloud ...

In recent years, since scale-up machines are not economical and may not be affordable for small businesses, scale-out has become the standard answer to data analysis, machine learning, and many other fields. However, these frameworks introduce complex ...

Causally consistent distributed storage systems have received significant attention due to the potential for providing high throughput. Global stabilization is a technique established for achieving causal consistency in distributed multi-version key-...

The focus of this paper is on causal consistency in a partially replicated distributed shared memory (DSM) system that provides the abstraction of shared read/write registers. Maintaining causal consistency in distributed shared memory systems has ...

Scale-out has become the standard answer to data analysis, machine learning and many other fields. Contrary to common belief, scale-up machines can outperform scale-out clusters for a considerable portion of tasks. However, those scale-up machines are ...

Distributed shared memory systems maintain multiple replicas of the shared memory registers. Maintaining causal consistency in such systems has received significant attention in the past. However, much of the previous literature focuses on \em full ...

Next-generation non-volatile memories (NVMs) will provide byte addressability, persistence, high density, and DRAM-like performance. They have the potential to benefit many datacenter applications. However, most previous research on NVMs has focused on ...

Causal consistency is one of the widely used consistency models in wide-area replicated systems due to highly scalable semantics. Partial replication is a replication mechanism that emphasizes a better network capacity utilization. However, it has a ...

This paper presents a memory allocator targeting manycore architec- tures with distributed memory. Among the family of Multi Processor System on Chip (MPSoC), these devices are composed of multiple nodes linked by an on-chip network; most nodes have ...

Maintaining a scalable high-performance virtual global address space using distributed memory hardware has proven to be challenging. In this paper we evaluate a new approach for such an active global address space that leverages the capabilities of the ...

Smart Cyber-Physical Systems (SCPS) aim not only at integrating computational platforms and physical processes, but also at creating larger "systems of systems" capable of satisfying multiple critical constraints such as energy efficiency, high-...

Many modern large graph and Big Data processing applications operate on datasets that do not fit into DRAM of a single machine. This leads to a design of scale-out applications, where the application dataset is partitioned and processed by a cluster of ...

The shared memory model helps parallel programming productivity, but it also has a high hardware cost and imposes scalability constraints. Ultimately, higher performance will use distributed memories, which scales better but requires programmers to ...

In geo-replicated systems and the cloud, data replication provides fault tolerance and low latency. Causal consistency in such systems is an interesting consistency model. Most existing works assume the data is fully replicated because this greatly ...

Coordinating mobile robots are widely used in commercial and industrial settings to fulfill various tasks. However, to program the coordination among mobile robots is challenging. A coordination framework is needed to shield the programmer from handling ...

Data replication is commonly used for fault tolerance in reliable distributed systems. In this paper, we propose three optimal protocols for causal consistency in distributed shared memory systems. Our proposed optimal protocols are designed for partial ...