JUSUF: Modular Tier-2 Supercomputing and Cloud Infrastructure at Jülich Supercomputing Centre

JUSUF is a petaflop supercomputer operated by Jülich Supercomputing Centre at Forschungszentrum Jülich as a European supercomputing and cloud resource. JUSUF was funded via the ICEI project and especially serves the Human Brain Project and PRACE via ICEI and the Fenix Research Infrastructure. The system consists of two parts, an HPC cluster partition and an Infrastructure-as-a-Service cloud partition. The system entered production phase in spring 2020. It is based on the Bull X400 product family with AMD Rome processors, partially accelerated by Nvidia V100 GPUs, and Nvidia Mellanox HDR InfiniBand.

IMPLEMENTASI CLOUD COMPUTING SEBAGAI RADIUS SERVER PADA JARINGAN INTERNET ROUTER MIKROTIK

Banyaknya pengguna internet pada suatu tempat atau instansi menimbulkan sebuah antrian yang menyebabkan sulitnya pengguna dalam mengakses internet. Berdasarkan masalah tersebut penulis mengimplementasikan cloud computing sebagai radius server pada jaringan internet dengan menggunakan Router MikroTik sebagai alat manajemen bandwith, RADIUS (Remote Authentication Dial-In User Service) server akan dibangun didalam server Ubuntu dengan memanfaatkan service cloud computing dari AWS (Amazon WEB Service), selain sebagai RADIUS server, Dengan adanya RADIUS server yang dibangun dengan cloud computing dan Router MikroTik stabilitas jaringan internet pada suatu tempat atau instansi menjadi lebih baik dan proses manajemen pengguna menjadi mudah.

A Traceability Public Service Cloud Platform Incorporating IDcode System and Colorful QR Code Technology for Important Product

At present, the epidemic situation of COVID-19 is raging rampantly in the whole world, affecting the hearts of billions of people. The new coronavirus has been detected in many foods and agricultural products. At the same time, vaccines and medicines to prevent or treat COVID-19 are also stepping up research and development and gradually put into use. The quality and safety of foods, medicines, and agricultural products are directly related to the lives and health of people. There are many potential dangers and hidden risks of accidents in the production, sale, and transportation of dangerous goods and special equipment. Therefore, it is necessary to effectively monitor and record the workflow of the above productions or goods. In this paper, we developed an important product traceability public service cloud platform (IPTPSCP) based on batch identification and record keeping with International Two-Dimensional Code Object Identifier System (IDcode) coding rules. Through a case study of the tea factory that produces and sells Xinyang Maojian tea, a test and implementation of IPTPSCP was shown by designing a colorful QR code to prevent the traceability information from being forged in batches. Judging from the overall effect of the practical application of more than a dozen settled enterprises, IPTPSCP has improved the efficiency of data collection and monitoring by about 13%. The results show that the IPTPSCP can be considered as an effective tool to guarantee the quality and safety of products. Besides, since it is not required for the enterprise to invest much money and manpower to develop software, IPTPSCP reduces the cost of implementing product traceability by about 36%.

CacheInspector

Infrastructure-as-a-Service cloud providers sell virtual machines that are only specified in terms of number of CPU cores, amount of memory, and I/O throughput. Performance-critical aspects such as cache sizes and memory latency are missing or reported in ways that make them hard to compare across cloud providers. It is difficult for users to adapt their application’s behavior to the available resources. In this work, we aim to increase the visibility that cloud users have into shared resources on public clouds. Specifically, we present CacheInspector , a lightweight runtime that determines the performance and allocated capacity of shared caches on multi-tenant public clouds. We validate CacheInspector ’s accuracy in a controlled environment, and use it to study the characteristics and variability of cache resources in the cloud, across time, instances, availability regions, and cloud providers. We show that CacheInspector ’s output allows cloud users to tailor their application’s behavior, including their output quality, to avoid suboptimal performance when resources are scarce.