Related papers: Exploring DAOS Interfaces and Performance
The next generation of AI applications will continuously interact with the environment and learn from these interactions. These applications impose new and demanding systems requirements, both in terms of performance and flexibility. In…
A flexible and highly-extensible data assimilation testing suite, named DATeS, is described in this paper. DATeS aims to offer a unified testing environment that allows researchers to compare different data assimilation methodologies and…
Workflow and serverless frameworks have empowered new approaches to distributed application design by abstracting compute resources. However, their typically limited or one-size-fits-all support for advanced data flow patterns leaves…
With the advent of hundreds of cores on a chip to accelerate applications, the operating system (OS) needs to exploit the existing parallelism provided by the underlying hardware resources to determine the right amount of processes to be…
All Control Systems that grow to any size have a variety of data that are stored in different formats on different nodes in the network. Examples include sensor value and status, archived sensor data, device oriented support data and…
Multi-sensor fusion significantly enhances the accuracy and robustness of 3D semantic occupancy prediction, which is crucial for autonomous driving and robotics. However, most existing approaches depend on high-resolution images and complex…
Since there are a number of Internet-of-Things (IoT) applications that need to collect data sets from a large number of sensors or devices in real-time, sensing and communication need to be integrated for efficient uploading from devices.…
Real-Time availability of information is of most importance in large scale distributed interactive simulation in network-centric communication. Information generated from multiple federates must be distributed and made available to…
Data Access will be the next generation data abstraction layer for EPICS. Its implementation in C++ brought up a number of issues that are related to object oriented technology's impact on CPU and memory usage. What is gained by the new…
The ability to store multiple versions of a data item is a powerful primitive that has had a wide variety of uses: relational databases, transactional memory, version control systems, to name a few. However, each implementation uses a very…
We present DISco, a storage and communication middleware designed to enable distributed and task-centric autonomic control of networks. DISco is designed to enable multi-agent identification of anomalous situations -- so-called "challenges"…
The Object Store model has quickly become the basis of most commercially successful mass storage infrastructure, backing so-called "Cloud" storage such as Amazon S3, but also underlying the implementation of most parallel distributed…
Several Network Operating Systems (NOS) have been proposed in the last few years for Software Defined Networks; however, a few of them are currently offering the resiliency, scalability and high availability required for production…
The adoption of very low latency persistent memory modules (PMMs) upends the long-established model of disaggregated file system access. Instead, by colocating computation and PMM storage, we can provide applications much higher I/O…
We propose CFS, a distributed file system for large scale container platforms. CFS supports both sequential and random file accesses with optimized storage for both large files and small files, and adopts different replication protocols for…
Decentralized autonomous organizations (DAOs) are emerging innovative organizational structures, enabling collective coordination, and reshaping digital collaboration. Despite the promising and transformative characteristics of DAOs, the…
This work describes the design, implementation and performance analysis of a distributed two-tiered storage software. The first tier functions as a distributed software cache implemented using solid-state devices~(NVMes) and the second tier…
Decentralized Autonomous Organizations (DAOs) have seen exponential growth and interest due to their potential to redefine organizational structure and governance. Despite this, there is a discrepancy between the ideals of autonomy and…
The Distributed object computing is a paradigm that allows objects to be distributed across a heterogeneous network, and allows each of the components to interoperate as a unified whole. A new generation of distributed applications, such as…
Scaling deep neural network (DNN) training to more devices can reduce time-to-solution. However, it is impractical for users with limited computing resources. FOSI, as a hybrid order optimizer, converges faster than conventional optimizers…