Related papers: A distributed file system for a wide-area high per…
FPGAs (Field Programmable Gate arrays) have gained massive popularity today as accelerators for a variety of workloads, including big data analytics, and parallel and distributed computing. This has fueled the study of mechanisms to…
Online analytical processing of queries on datasets in the many-terabyte range is only possible with costly distributed computing systems. To decrease the cost and increase the throughput, systems can leverage accelerators such as GPUs,…
Data centers have become center of big data processing. Most programs running in a data center processes big data. The storage requirements of such programs cannot be fulfilled by a single node in the data center, and hence a distributed…
Advances in networks, accelerators, and cloud services encourage programmers to reconsider where to compute -- such as when fast networks make it cost-effective to compute on remote accelerators despite added latency. Workflow and…
This paper presents a general xml-based distributed software architecture in the aim of accessing and sharing resources in an opened client/server environment. The paper is organized as follows : First, we introduce the idea of a "General…
This paper presents a multi-cloud networking architecture built on zero trust principles and micro-segmentation to provide secure connectivity with authentication, authorization, and encryption in transit. The proposed design includes the…
The provision of mechanisms for processor allocation in current distributed parallel programming models is very limited. This makes difficult, or even prohibits, the expression of a large class of programs which require a run-time…
Shared folders are still a common practice for granting third parties access to data files, regardless of the advances in data sharing technologies. Services like Google Drive, Dropbox, Box, and others, provide infrastructures and…
Decentralized data storage systems like the Interplanetary Filesystem (IPFS) are becoming increasingly popular, e. g., as a data layer in blockchain applications and for sharing content in a censorship-resistant manner. In IPFS, data is…
Foundation models have demonstrated remarkable success across diverse domains and tasks, primarily due to the thrive of large-scale, diverse, and high-quality datasets. However, in the field of medical imaging, the curation and assembling…
The Target infrastructure has been specially built as a storage and compute infrastructure for the information systems derived from Astro-WISE. This infrastructure will be used by several applications that collaborate in the area of…
Scientific datasets are known for their challenging storage demands and the associated processing pipelines that transform their information. Some of those processing tasks include filtering, cleansing, aggregation, normalization, and data…
In order to associate complex traits with genetic polymorphisms, genome-wide association studies process huge datasets involving tens of thousands of individuals genotyped for millions of polymorphisms. When handling these datasets, which…
Rapid advancements in cloud based platforms providing access to quantum computing capabilities have opened up several challenges for efficient usage of these highly delicate and costly devices. Although most of the current systems use a…
The Network Function Virtualization (NFV) paradigm has been devised as an enabler of next generation network infrastructures by speeding up the provisioning and the composition of novel network services. The latter are implemented via a…
Many extreme-scale applications require the movement of large quantities of data to, from, and among leadership computing facilities, as well as other scientific facilities and the home institutions of facility users. These applications,…
Recent improvements in both the performance and scalability of shared-nothing, transactional, in-memory NewSQL databases have reopened the research question of whether distributed metadata for hierarchical file systems can be managed using…
We describe the political and technical complications encountered during the astronomical CosmoGrid project. CosmoGrid is a numerical study on the formation of large scale structure in the universe. The simulations are challenging due to…
Graphs are central to modeling relationships in scientific computing, data analysis, and AI/ML, but their growing scale can exceed the memory and compute capacity of single nodes, requiring distributed solutions. Existing distributed graph…
The increasing adoption of Cloud-based data processing and storage poses a number of privacy issues. Users wish to preserve full control over their sensitive data and cannot accept it to be fully accessible to an external storage provider.…