Related papers: Open and Free Cluster for Public
We introduce a new approach to enable an open and public parallel machine which is accessible for multi users with multi jobs belong to different blocks running at the same time. The concept is required especially for parallel machines…
The openPC is a set of open source tools that realizes a parallel machine and distributed computing environment divisible into several independent blocks of nodes, and each of them is remotely but fully in any means accessible for users…
A web-based interface dedicated for cluster computer which is publicly accessible for free is introduced. The interface plays an important role to enable secure public access, while providing user-friendly computational environment for…
We have developed a monitoring and control system for LIPI's Public Cluster. The system consists of microcontrollers and full web-based user interfaces for daily operation. It is argued that, due to its special natures, the cluster requires…
We present extended multi block approach in the LIPI Public Cluster. The multi block approach enables a cluster to be divided into several independent blocks which run jobs owned by different users simultaneously. Previously, we have…
We present the architecture and application of the distributed control in public cluster, a parallel machine which is open for public access. Following the nature of public cluster, the integrated distributed control system is fully…
The tremendous advance in computer technology in the past decade has made it possible to achieve the performance of a supercomputer on a very small budget. We have built a multi-CPU cluster of Pentium PC capable of parallel computations…
HEP Cluster is designed and implemented in Scientific Linux Cern 5.5 to grant High Energy Physics researchers one place where they can go to undertake a particular task or to provide a parallel processing architecture in which CPU resources…
The transparency nature of Open Data is beneficial for citizens to evaluate government work performance. In Indonesia, each government bodies or ministry have their own standard operating procedure on data treatment resulting in incoherent…
Despite the de-facto technological uniformity fostered by the cloud and edge computing paradigms, resource fragmentation across isolated clusters hinders the dynamism in application placement, leading to suboptimal performance and…
Since January 1, 2005 we have launched "OPTO" Portal, a website dedicated to optical communities in Indonesia. The address of this portal is http://www.opto.lipi.go.id and is self-supporting managed and not for commercial purposes. Our aims…
Cluster computing is not a new area of computing. It is, however, evident that there is a growing interest in its usage in all areas where applications have traditionally used parallel or distributed computing platforms. The growing…
Recent advances in computer architecture and networking opened the opportunity for parallelizing the clustering algorithms. This divide-and-conquer strategy often results in better results to centralized clustering with a much-improved time…
In this report, I describe the design and implementation of an inexpensive, eight node, 32 core, cluster of raspberry pi single board computers, as well as the performance of this cluster on two computational tasks, one that requires…
This paper describes BlockPKI, a blockchain-based public-key infrastructure that enables an automated, resilient, and transparent issuance of digital certificates. Our goal is to address several shortcomings of the current TLS…
State machine replication is standard approach to fault tolerance. One of the key assumptions of state machine replication is that replicas must execute operations deterministically and thus serially. To benefit from multi-core servers,…
We present a simple library which equips MPI implementations with truly asynchronous non-blocking point-to-point operations, and which is independent of the underlying communication infrastructure. It utilizes the MPI profiling interface…
As ML applications are becoming ever more pervasive, fully-trained systems are made increasingly available to a wide public, allowing end-users to submit queries with their own data, and to efficiently retrieve results. With increasingly…
Amid the rapid advancements in large machine learning (ML) models, universities worldwide are investing substantial funds and efforts into GPU clusters. However, managing a shared GPU cluster poses a pyramid of challenges, from hardware…
Open source projects have made incredible progress in producing transparent and widely usable machine learning models and systems, but open source alone will face challenges in fully democratizing access to AI. Unlike software, AI models…