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The Hadoop scheduler is a centerpiece of Hadoop, the leading processing framework for data-intensive applications in the cloud. Given the impact of failures on the performance of applications running on Hadoop, testing and verifying the…
We propose an approach for improved reproducibility that includes capturing and relating provenance characteristics and performance metrics, in a hybrid queriable system, the ProvEn server. The system capabilities are illustrated on two use…
Planning for an upcoming project iteration (sprint) is one of the key activities in Scrum planning. In this paper, we present our work in progress on exploring the applicability of Large Language Models (LLMs) for solving this problem. We…
The under exploitation of the available resources risks to be one of the main problems for a computing center. The growing demand of computational power necessarily entails more complex approaches in the management of the computing…
A range of computational biology software (GROMACS, AMBER, NAMD, LAMMPS, OpenMM, Psi4 and RELION) was benchmarked on a representative selection of HPC hardware, including AMD EPYC 7742 CPU nodes, NVIDIA V100 and AMD MI250X GPU nodes, and an…
Despite the great advance of Multimodal Large Language Models (MLLMs) in both instruction dataset building and benchmarking, the independence of training and evaluation makes current MLLMs hard to further improve their capability under the…
In this paper, we introduce a software-defined framework that enables the parallel utilization of all the programmable processing resources available in heterogeneous system-on-chip (SoC) including FPGA-based hardware accelerators and…
We introduce the Balsam service to manage high-throughput task scheduling and execution on supercomputing systems. Balsam allows users to populate a task database with a variety of tasks ranging from simple independent tasks to dynamic…
The proliferation of heterogeneous chip multiprocessors in recent years has reached unprecedented levels. Traditional homogeneous platforms have shown fundamental limitations when it comes to enabling high-performance yet-ultra-low-power…
GPU-based HPC clusters are attracting more scientific application developers due to their extensive parallelism and energy efficiency. In order to achieve portability among a variety of multi/many core architectures, a popular choice for an…
The Preconditioned Conjugate Gradient method is often employed for the solution of linear systems of equations arising in numerical simulations of physical phenomena. While being widely used, the solver is also known for its lack of…
Task graphs have been studied for decades as a foundation for scheduling irregular parallel applications and incorporated in programming models such as OpenMP. While many high-performance parallel libraries are based on task graphs, they…
In the load balancing problem, introduced by Graham in the 1960s (SIAM J. of Appl. Math. 1966, 1969), jobs arriving online have to be assigned to machines so to minimize an objective defined on machine loads. A long line of work has…
Data replication technologies enable efficient and highly-available data access, thus gaining more and more interests in both the academia and the industry. However, data replication introduces the problem of data consistency. Modern…
Large language models (LLMs) and agentic systems have recently demonstrated potential for automating scientific workflows, including atomistic simulations. However, their deployment in high-performance computing (HPC) environments remains…
Demand for enterprise data warehouse solutions to support real-time Online Transaction Processing (OLTP) queries as well as long-running Online Analytical Processing (OLAP) workloads is growing. Greenplum database is traditionally known as…
Traditionally, on-demand, rigid, and malleable applications have been scheduled and executed on separate systems. The ever-growing workload demands and rapidly developing HPC infrastructure trigger the interest of converging these…
In cloud computing environments, a large number of users access data stored in highly available storage systems. To provide good performance to geographically disperse users and allow operation even in the presence of failures or network…
In today's Web and social network environments, query workloads include ad hoc and OLAP queries, as well as iterative algorithms that analyze data relationships (e.g., link analysis, clustering, learning). Modern DBMSs support ad hoc and…
Extreme dynamic heterogeneity in high performance computing systems and the convergence of traditional HPC with new simulation, analysis, and data science approaches impose increasingly more complex requirements on resource and job…