Performance Characterization of Multi-threaded Graph Processing Applications on Intel Many-Integrated-Core Architecture

Intel Xeon Phi many-integrated-core (MIC) architectures usher in a new era of terascale integration. Among emerging killer applications, parallel graph processing has been a critical technique to analyze connected data. In this paper, we empirically evaluate various computing platforms including an Intel Xeon E5 CPU, a Nvidia Geforce GTX1070 GPU and an Xeon Phi 7210 processor codenamed Knights Landing (KNL) in the domain of parallel graph processing. We show that the KNL gains encouraging performance when processing graphs, so that it can become a promising solution to accelerating multi-threaded graph applications. We further characterize the impact of KNL architectural enhancements on the performance of a state-of-the art graph framework.We have four key observations: 1 Different graph applications require distinctive numbers of threads to reach the peak performance. For the same application, various datasets need even different numbers of threads to achieve the best performance. 2 Only a few graph applications benefit from the high bandwidth MCDRAM, while others favor the low latency DDR4 DRAM. 3 Vector processing units executing AVX512 SIMD instructions on KNLs are underutilized when running the state-of-the-art graph framework. 4 The sub-NUMA cache clustering mode offering the lowest local memory access latency hurts the performance of graph benchmarks that are lack of NUMA awareness. At last, We suggest future works including system auto-tuning tools and graph framework optimizations to fully exploit the potential of KNL for parallel graph processing.Comment: published as L. Jiang, L. Chen and J. Qiu, "Performance Characterization of Multi-threaded Graph Processing Applications on Many-Integrated-Core Architecture," 2018 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), Belfast, United Kingdom, 2018, pp. 199-20

Experimental analysis for the effect of dynamic capillarity on stress transformation in porous silicon

The evolution of real-time stress in porous silicon(PS) during drying is investigated using micro-Raman spectroscopy. The results show that the PS sample underwent non-negligible stress when immersed in liquid and suffered a stress impulsion during drying. Such nonlinear transformation and nonhomogeneneous distribution of stress are regarded as the coupling effects of several physical phenomena attributable to the intricate topological structure of PS. The effect of dynamic capillarity can induce microcracks and even collapse in PSstructures during manufacture and storage.This work is funded by the National Natural Science Foundation of China Contract Nos. 10732080 and 10502014

THE HISTONE DEMETHYLASE KDM4B CONTRIBUTES TO THE PERITONEAL DISSEMINATION OF OVARIAN CANCER

Solid tumors contain hypoxic regions due to their unchecked proliferation. This hypoxic microenvironment induces cancer cell metastasis and angiogenesis to promote tumor survival. The hypoxia-inducible factors (HIFs) are the primary regulators of the hypoxic response, inducing genes involved in important tumor progression pathways. The lysine (K)-specific demethylase KDM4B is a direct target of HIF, creating an intriguing link between the hypoxic tumor microenvironment and downstream gene expression beyond the direct actions of HIF stabilization. The findings that hypoxia-inducible KDM4B overexpression occurs in multiple cancer types suggest a general KDM4B function in these cancers. However, our current knowledge on KDM4B function in each cancer type seems to rely on tissue-specific pathways. In a microarray analysis using transient knockdown of KDM4B, we identified a set of potential KDM4B targets with clear associations to tumor cell growth, migration, and metastasis. Microarray data from HCT116 colon carcinoma, SKOV3ip.1 ovarian cancer and RCC4 renal cell carcinoma cells identified numerous genes specifically regulated in each cell type, as well as 16 common targets shared by all three cell lines. Through Ingenuity Pathway Analysis, we found that KDM4B also regulated different pathways under different oxygen conditions. In general, KDM4B regulated proliferative genes in normoxia, and metastatic genes in hypoxia. We have also demonstrated that KDM4B regulated these target genes by binding and demethylating near the promoter regions of these genes. Our findings suggest that KDM4B regulates pathways specific to each cancer type and tumor microenvironment to support cancer cell survival. Hypoxia has been linked to poor prognosis of epithelial ovarian cancer (EOC), likely through regulating genes that contribute to the widespread dissemination of peritoneal metastases observed in late-stage diagnosis. In this study, we have shown that KDM4B is expressed in high grade serous adenocarcinoma and EOC cell lines, especially in hypoxia. Suppressing KDM4B inhibits ovarian cancer cell invasion, migration and spheroid formation in vitro. KDM4B is also crucial for seeding and growth of peritoneal tumors in vivo, where its expression corresponds to hypoxic regions. Thus, KDM4B is a potent contributor to the seeding and growth of peritoneal tumors, one of the predominant factors affecting prognosis of EOC