This article studies mini-applications—Minisweep, GenASiS, GPP, and FF—that use computational methods commonly encountered in HPC. We have ported these applications to develop OpenACC and OpenMP versions, and evaluated their performance on Titan (Cray XK7 with K20x GPUs), Cori (Cray XC40 with Intel KNL), Summit (IBM AC922 with Volta GPUs), and Cori-GPU (Cray CS-Storm 500NX with Intel Skylake and Volta GPUs). Our goals are for these new ports to be useful to both application and compiler developers, to document and describe the lessons learned and the methodology to create optimized OpenMP and OpenACC versions, and to provide a description of possible migration paths between the two specifications. Cases where specific directives or code patterns result in improved performance for a given architecture are highlighted. We also include discussions of the functionality and maturity of the latest compilers available on the above platforms with respect to OpenACC or OpenMP implementations.

Osteosarcoma (OSA) is a highly aggressive and metastatic neoplasm of both the canine and human patient and is the leading form of osseous neoplasia in both species worldwide. To gain deeper insight into the heterogeneous and genetically chaotic nature of OSA, we applied single-cell transcriptome (scRNA-seq) analysis to 4 canine OSA cell lines. This novel application of scRNA-seq technology to the canine genome required uploading the CanFam3.1 reference genome into an analysis pipeline (10X Genomics Cell Ranger); this methodology has not been reported previously in the canine species, to our knowledge. The scRNA-seq outputs were validated by comparing them to cDNA expression from reverse-transcription PCR (RT-PCR) and Sanger sequencing bulk analysis of 4 canine OSA cell lines (COS31, DOUG, POS, and HMPOS) for 11 genes implicated in the pathogenesis of canine OSA. The scRNA-seq outputs revealed the significant heterogeneity of gene transcription expression patterns within the cell lines investigated (COS31 and DOUG). The scRNA-seq data showed 10 distinct clusters of similarly shared transcriptomic expression patterns in COS31; 12 clusters were identified in DOUG. In addition, cRNA-seq analysis provided data for integration into the Qiagen Ingenuity Pathway Analysis software for canonical pathway analysis. Of the 81 distinct pathways identified within the clusters, 33 had been implicated in the pathogenesis of OSA, of which 18 had not been reported previously in canine OSA.