Related papers: A Data as a Service (DaaS) Model for GPU-based Dat…
Workflow management systems (WMS) support the composition and deployment of workflow-oriented applications in distributed computing environments. They hide the complexity of managing large-scale applications, which includes the controlling…
This paper explores the architecture of Software as a Service (SaaS) platforms, emphasizing scalability and maintainability. SaaS, a flexible software distribution model suitable for individuals and organizations, has become prevalent with…
Serverless computing is an emerging cloud computing paradigm that can reduce costs for cloud providers and their customers. However, serverless cloud platforms have stringent performance requirements (due to the need to execute short…
While prior researches focus on CPU-based microservices, they are not applicable for GPU-based microservices due to the different contention patterns. It is challenging to optimize the resource utilization while guaranteeing the QoS for GPU…
Due to the surge in the volume of data generated and rapid advancement in Artificial Intelligence (AI) techniques like machine learning and deep learning, the existing traditional computing models have become inadequate to process an…
Commercial autonomous machines is a thriving sector, one that is likely the next ubiquitous computing platform, after Personal Computers (PC), cloud computing, and mobile computing. Nevertheless, a suitable computing substrate for…
Function-as-a-Service (FaaS) is a recent and already very popular paradigm in cloud computing. The function provider need only specify the function to be run, usually in a high-level language like JavaScript, and the service provider…
Large language model (LLM) inference has become a dominant workload in modern data centers, driving significant GPU utilization and energy consumption. While prior systems optimize throughput and latency by batching, scheduling, and…
The rising demand for generative large language models (LLMs) poses challenges for thermal and power management in cloud datacenters. Traditional techniques often are inadequate for LLM inference due to the fine-grained, millisecond-scale…
Cloud applications are increasingly shifting from large monolithic services, to large numbers of loosely-coupled, specialized microservices. Despite their advantages in terms of facilitating development, deployment, modularity, and…
In hosting environments such as IaaS clouds, desirable application performance is usually guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated for use…
On the rise of distributed computing technologies, video big data analytics in the cloud have attracted researchers and practitioners' attention. The current technology and market trends demand an efficient framework for video big data…
For the past two decades, the DB community has devoted substantial research to take advantage of cheap clusters of machines for distributed data analytics -- we believe that we are at the beginning of a paradigm shift. The scaling laws and…
Cloud monitoring activity involves dynamically tracking the Quality of Service (QoS) parameters related to virtualized resources (e.g., VM, storage, network, appliances, etc.), the physical resources they share, the applications running on…
The graphics processing unit (GPU) has emerged as a powerful and cost effective processor for general performance computing. GPUs are capable of an order of magnitude more floating-point operations per second as compared to modern central…
The cloud computing technology uses datacenters, which require energy. Recent trends show that the required energy for these datacenters will rise over time, or at least remain constant. Hence, the scientific community developed different…
Caches are an important component of modern computing systems given their significant impact on performance. In particular, caches play a key role in the cloud due to the nature of large-scale, data-intensive processing. One of the key…
The rapid expansion of AI inference services in the cloud necessitates a robust scalability solution to manage dynamic workloads and maintain high performance. This study proposes a comprehensive scalability optimization framework for cloud…
Serverless Function-as-a-Service (FaaS) platforms provide applications with resources that are highly elastic, quick to instantiate, accounted at fine granularity, and without the need for explicit runtime resource orchestration. This…
Beowulf clusters are very popular and deployed worldwide in support of scientific computing, because of the high computational power and performance. However, they also pose several challenges, and yet they need to provide high…