swTVM: Exploring the Automated Compilation for Deep Learning on Sunway Architecture

The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application portability. Among the exiting deep learning compilers, TVM is well known for its efficiency in code generation and optimization across diverse hardware devices. In the meanwhile, the Sunway many-core processor renders itself as a competitive candidate for its attractive computational power in both scientific and deep learning applications. This paper combines the trends in these two directions. Specifically, we propose swTVM that extends the original TVM to support ahead-of-time compilation for architecture requiring cross-compilation such as Sunway. In addition, we leverage the architecture features during the compilation such as core group for massive parallelism, DMA for high bandwidth memory transfer and local device memory for data locality, in order to generate efficient code for deep learning application on Sunway. The experimental results show the ability of swTVM to automatically generate code for various deep neural network models on Sunway. The performance of automatically generated code for AlexNet and VGG-19 by swTVM achieves 6.71x and 2.45x speedup on average than hand-optimized OpenACC implementations on convolution and fully connected layers respectively. This work is the first attempt from the compiler perspective to bridge the gap of deep learning and high performance architecture particularly with productivity and efficiency in mind. We would like to open source the implementation so that more people can embrace the power of deep learning compiler and Sunway many-core processor

Association between mesothelin expression and survival outcomes in patients with triple-negative breast cancer: a protocol for a systematic review

PRISMA flow diagram [14]. (DOCX 98 kb

Urban-Rural Disparity in Cancer Incidence, Mortality, and Survivals in Shanghai, China, During 2002 and 2015

Introduction: Disparities in the incidence, mortality, and survival of cancer types between urban and rural areas in China reflect the effects of different risk factor exposure, education, and different medical availability. We aimed to characterize the disparities in the incidence, mortality, and survivals of cancer types between urban and rural areas in Shanghai, China, 2002-2015.Materials and Methods: The incidence and mortality were standardized by Segi's world standard population. Trends in the incidence and mortality of cancers were compared using annual percent change. The 5-year observed and relative survivals were calculated with life table and Ederer II methods.Results: Age-standardized incidences and mortalities were 212.55/105 and 109.45/105 in urban areas and 210.14/105 and 103.99/105 in rural areas, respectively. Female breast cancer and colorectal cancer occurred more frequently in urban than in rural areas, quite in contrast to liver cancer and cervical cancer. Cancers of lung and bronchus, liver, stomach, and colon and rectum were the leading causes of cancer death in both areas. Age-standardized incidence of female breast cancer and colorectal cancer in urban areas increased while gastric cancer and liver cancer decreased in both areas. Age-standardized mortalities of cancers of breast, esophagus, stomach, colon and rectum, liver, and lung and bronchus decreased in both areas. For all cancers combined, the 5-year observed and relative survivals of cancer patients were higher in urban than in rural areas. The 5-year observed and relative survivals of cancers of liver, pancreas, stomach, brain and central nervous system (CNS), and prostate were higher in urban than in rural areas. The 5-year observed and relative survivals of cervical cancer were higher in rural than in urban areas.Conclusions: Factors promoting female breast cancer and colorectal cancer in urban areas and liver cancer and cervical cancer in rural areas should be specifically intervened in cancer prophylaxis. Improved medical services can greatly prolong the survival of major cancers in rural areas

QTL Mapping of Fiber-Related Traits Based on a High-Density Genetic Map in Flax (Linum usitatissimum L.)

A genetic map is an important and valuable tool for quantitative trait locus (QTL) mapping, marker-assisted selection (MAS)-based breeding, and reference-assisted chromosome assembly. In this study, 112 F2 plants from a cross between Linum usitatissimum L. “DIANE” and “NY17” and parent plants were subjected to high-throughput sequencing and specific-locus amplified fragment (SLAF) library construction. After preprocessing, 61.64 Gb of raw data containing 253.71 Mb paired-end reads, each 101 bp in length, were obtained. A total of 192,797 SLAFs were identified, of which 23,115 were polymorphic, with a polymorphism rate of 11.99%. Finally, 2,339 SLAFs were organized into a linkage map consisting of 15 linkage groups (LGs). The total length of the genetic map was 1483.25 centimorgans (cM) and the average distance between adjacent markers was 0.63 cM. Combined with flax chromosome-scale pseudomolecules, 12 QTLs associating with 6 flax fiber-related traits were mapped on the chromosomal scaffolds. This high-density genetic map of flax should serve as a foundation for flax fine QTL mapping, draft genome assembly, and MAS-guided breeding. Ultimately, the genomic regions identified in this research could potentially be valuable for improving flax fiber cultivars, as well as for identification of candidate genes involved in flax fiber formation processes.Significance statementA high-density genetic map of flax was constructed, and QTLs were identified on the sequence scaffolds to be interrelated with fiber-related traits. The results of this study will not only provide a platform for gene/QTL fine mapping, map-based gene isolation, and molecular breeding for flax, but also provide a reference to help position sequence scaffolds on the physical map and assist in the process of assembling the flax genome sequence

A genetic study and meta-analysis of the genetic predisposition of prostate cancer in a Chinese population.

Prostate cancer predisposition has been extensively investigated in European populations, but there have been few studies of other ethnic groups. To investigate prostate cancer susceptibility in the under-investigated Chinese population, we performed single-nucleotide polymorphism (SNP) array analysis on a cohort of Chinese cases and controls and then meta-analysis with data from the existing Chinese prostate cancer genome-wide association study (GWAS). Genotyping 211,155 SNPs in 495 cases and 640 controls of Chinese ancestry identified several new suggestive Chinese prostate cancer predisposition loci. However, none of them reached genome-wide significance level either by meta-analysis or replication study. The meta-analysis with the Chinese GWAS data revealed that four 8q24 loci are the main contributors to Chinese prostate cancer risk and the risk alleles from three of them exist at much higher frequencies in Chinese than European populations. We also found that several predisposition loci reported in Western populations have different effect on Chinese men. Therefore, this first extensive single-nucleotide polymorphism study of Chinese prostate cancer in comparison with European population indicates that four loci on 8q24 contribute to a great risk of prostate cancer in a considerable large proportion of Chinese men. Based on those four loci, the top 10% of the population have six- or two-fold prostate cancer risk compared with men of the bottom 10% or median risk respectively, which may facilitate the design of prostate cancer genetic risk screening and prevention in Chinese men. These findings also provide additional insights into the etiology and pathogenesis of prostate cancer.This work was conducted on behalf of the CHIPGECS and The PRACTICAL consortia (see Supplementary Consortia). We acknowledge the contribution of doctors, nurses and postgraduate research students at the CHIPGENCS sample collecting centers. We thank Orchid and Rosetrees for funding support. This work was also supported by National Natural Science foundation of China for funding support to H Zhang (Grant No: 30671793 and 81072377), N Feng (Grant No: 81272831), X Zhang (Grant No: 30572139, 30872924 and 81072095), S Zhao (Grant No: 81072092 and 81328017), Y Yu (Grant No: 81172448) and Program for New Century Excellent Talents in University from Department of Education of China (NCET-08-0223) and the National High Technology Research and Development Program of China (863 Program 2012AA021101) to X Zhang.This is the final version of the article. It first appeared from Impact Journals via http://dx.doi.org/10.18632/oncotarget.725

Genomic monitoring of SARS-CoV-2 uncovers an Nsp1 deletion variant that modulates type I interferon response

The SARS-CoV-2 virus, the causative agent of COVID-19, is undergoing constant mutation. Here, we utilized an integrative approach combining epidemiology, virus genome sequencing, clinical phenotyping, and experimental validation to locate mutations of clinical importance. We identified 35 recurrent variants, some of which are associated with clinical phenotypes related to severity. One variant, containing a deletion in the Nsp1-coding region (D500-532), was found in more than 20% of our sequenced samples and associates with higher RT-PCR cycle thresholds and lower serum IFN-beta levels of infected patients. Deletion variants in this locus were found in 37 countries worldwide, and viruses isolated from clinical samples or engineered by reverse genetics with related deletions in Nsp1 also induce lower IFN-beta responses in infected Calu-3 cells. Taken together, our virologic surveillance characterizes recurrent genetic diversity and identified mutations in Nsp1 of biological and clinical importance, which collectively may aid molecular diagnostics and drug design.Peer reviewe