Purpose High performance computing (HPC) is used to solve complex calculations that personal computing devices are unable to handle. HPC offers the potential for small- and medium-size enterprises (SMEs) to engage in product innovation, service improvement and the optimization of resource allocation (Borstnar and Ilijas, 2019). However, the expensive infrastructure, maintenance costs and resource knowledge gaps that accompany the use of HPC can make it inaccessible to SMEs. By moving HPC to the cloud, SMEs can gain access to the infrastructure without the requirement of owning or maintaining it, but they will need to accept the terms and conditions of the cloud contract. This paper aims to improve how SMEs access HPC through the cloud by providing insights into the terms and conditions of HPC cloud contracts. Design/methodology/approach This paper adopts a systematic literature review by implementing a four-step approach. A comprehensive search was undertaken and results synthesized to enable this paper’s objectives to be met. Findings This paper proposes that SMEs could gain competitive advantage(s) by understanding their own needs and improving their contract negotiation abilities, service management skills and risk management abilities before accepting the terms and conditions of the cloud contract. Furthermore, a checklist, service-level agreement, easily ignored elements and risk areas are presented as guidance for SMEs when reviewing their HPC cloud contract(s). Originality/value While HPC cloud contracts are a niche research topic, it is one of the key factors influencing the ability of SMEs to access HPC through the cloud. It is, however, by no means a level playfield with SMEs at a distinct disadvantage because of not influencing the writing up of the HPC cloud contract. The added value of the paper is that it contributes to our overall understanding of the terms and conditions of HPC cloud contracts.

ObjectiveTo present the global research features and hotspots, and forecast the emerging trends by conducting a bibliometric analysis based on literature related to autophagy of pancreatic cancer from 2011 to 2022.MethodsThe literature data regarding autophagy of pancreatic cancer were retrieved and downloaded from the Web of Science Core Collection (WOSCC) from Clarivate Analytics on June 10th, 2022. VOSviewer (version 1.6.18) was used to perform the bibliometric analysis.ResultsA total of 616 studies written by 3993 authors, covered 45 countries and 871 organizations, published in 263 journals and co-cited 28152 references from 2719 journals. China (n=260, 42.2%) and the United States (n=211, 34.3%) were the most frequent publishers and collaborated closely. However, publications from China had a low average number of citations (25.35 times per paper). The output of University of Texas MD Anderson Cancer Center ranked the first with 26 papers (accounting for 4.2% of the total publications). Cancers (n=23, 3.7%; Impact Factor = 6.639) published most papers in this field and was very pleasure to accept related researches. Daolin Tang and Rui Kang published the most papers (n=18, respectively). The research hotspots mainly focused on the mechanisms of autophagy in tumor onset and progression, the role of autophagy in tumor apoptosis, and autophagy-related drugs in treating pancreatic cancer (especially combined therapy). The emerging topics were chemotherapy resistance mediated by autophagy, tumor microenvironment related to autophagy, autophagy-depended epithelial-mesenchymal transition (EMT), mitophagy, and the role of autophagy in tumor invasion.ConclusionAttention has been increasing in autophagy of pancreatic cancer over the past 12 years. Our results undoubtedly provide scholars with new clues and ideas in this field.