相关论文: Dockerization Impacts in Database Performance Benc…

Container startup latency is a critical performance metric for CI/CD pipelines, serverless computing, and auto-scaling systems, yet practitioners lack empirical guidance on how infrastructure choices affect this latency. We present a…

Benchmarking has driven scientific progress in Evolutionary Computation, yet current practices fall short of real-world needs. Widely used synthetic suites such as BBOB and CEC isolate algorithmic phenomena but poorly reflect the structure,…

In recent years, data-intensive applications have been increasingly deployed on cloud systems. Such applications utilize significant compute, memory, and I/O resources to process large volumes of data. Optimizing the performance and…

Virtualization enables information and communications technology industry to better manage computing resources. In this regard, improvements in virtualization approaches together with the need for consistent runtime environment, lower…

Quantization is a promising technique for reducing the bit-width of deep models to improve their runtime performance and storage efficiency, and thus becomes a fundamental step for deployment. In real-world scenarios, quantized models are…

Performance interference can occur when various services are executed over the same physical infrastructure in a cloud system. This can lead to performance degradation compared to the execution of services in isolation. This work proposes a…

Benchmarking is how the performance of a computing system is determined. Surprisingly, even for classical computers this is not a straightforward process. One must choose the appropriate benchmark and metrics to extract meaningful results.…

Data warehouse architectural choices and optimization techniques are critical to decision support query performance. To facilitate these choices, the performance of the designed data warehouse must be assessed, usually with benchmarks.…

Docker is a containerization service that allows for convenient deployment of websites, databases, applications' APIs, and machine learning (ML) models with a few lines of code. Studies have recently explored the use of Docker for deploying…

Linux containers have risen in popularity in the last few years, making their way to commercial IT service offerings (such as PaaS), application deployments, and Continuous Delivery/Integration pipelines within various development teams.…

Docker is a virtualization technique heavily used in the industry to build cloud-based systems. In the context of Docker, a system is said to be observable if engineers can get accurate information about its running state in production. In…

Docker offers an ecosystem that offers a platform for application packaging, distributing, and managing within containers. However, the Docker platform has not yet matured. Presently, Docker is less secured than virtual machines (VM) and…

ISP minimizes data transfer for analytics but faces challenges in adaptation and disaggregation. We propose DockerSSD, an ISP model leveraging OS-level virtualization and lightweight firmware to enable containerized data processing directly…

Cloud computing recently developed into a viable alternative to on-premises systems for executing high-performance computing (HPC) applications. With the emergence of new vendors and hardware options, there is now a growing need to…

Solving the software dependency issue under the HPC environment has always been a difficult task for both computing system administrators and application scientists. This work would like to tackle the issue by introducing the modern…

Operating System-level virtualization technology, or containers as they are commonly known, represents the next generation of light-weight virtualization, and is primarily represented by Docker. However, Docker's current design does not…

Comprehensive benchmarking of clustering algorithms is rendered difficult by two key factors: (i)~the elusiveness of a unique mathematical definition of this unsupervised learning approach and (ii)~dependencies between the generating models…

Containers improve the efficiency in application deployment and thus have been widely utilised on Cloud and lately in High Performance Computing (HPC) environments. Containers encapsulate complex programs with their dependencies in isolated…

Experimental evaluation is a major research methodology for investigating clustering algorithms and many other machine learning algorithms. For this purpose, a number of benchmark datasets have been widely used in the literature and their…

Data lakes have emerged as a flexible and scalable solution for storing and analyzing large volumes of heterogeneous data, including structured, semi-structured, and unstructured formats. Despite their growing adoption in both industry and…