The rapid growth of unstructured data has driven the widespread adoption of LSM-tree-based key-value stores (KV stores). The write amplification resulting from compaction in LSM-trees causes a performance bottleneck. Existing solutions attempt to address this issue through key-value separation strategies. However, these studies fail to optimize the memory components of LSM-trees or provide efficient garbage collection (GC) strategies that achieve high performance while minimizing CPU overhead. These limitations motivated TSYS School computer scientist Yi Zhou and researchers from Anhui University, Zhongguancun Laboratory and Auburn University to propose a GPGPU-empowered gradient data hierarchy and key-value separation for optimizing KV stores, named GDH+. In a study set to appear in a forthcoming issue of ACM Transactions on Architecture and Code Optimization , Zhou et al. utilize GPGPU acceleration for sorting and lushing operations, op...
Turner College professor of management Phil Bryant recently surpassed 3,500 career Google Scholar citations. Additionally, Google Scholar reports that his i10-index is equal to 15, meaning that Bryant has published 15 studies that have each garnered at least 10 citations. Google Scholar also reports an additional metric. This is a scholar’s h-index, which is the largest number, h, of a scholar’s publications that have each garnered at least h citations. Bryant’s h-index is 14, meaning that his 14 most-cited studies have each generated at least 14 citations. Bryant's top-cited publication is a 2010 study on retaining talent that appears in Academy of Management Perspectives . Another piece on the same subject – this one appearing in a 2013 issue of Compensation and Benefits Review – has garnered the second-most citations over Bryant’s career. Each of these studies was co-authored with David Allen of the University of Memphis, while the first of the two was also written with James V...