Parallelization and characterization of SIFT on multi-core systems

This paper parallelizes and characterizes an important computer vision application — Scale Invariant Feature Transform (SIFT) both on a Symmetric Multiprocessor (SMP) platform and a large scale Chip Multiprocessor (CMP) simulator. SIFT is an approach for extracting distinctive invariant features from images and has been widely applied. In many computer vision problems, a real-time or even super-real-time processing capability of SIFT is required. To meet the computation demand, we optimize and parallelize SIFT to accelerate its execution on multi-core systems. Our study shows that SIFT can achieve a 9.7x ~ 11x speedup on a 16-core SMP system. Furthermore, Single Instruction Multiple Data (SIMD) and cache-conscious optimization bring another 85 % performance gain at most. But it is still three times slower than the real-time requirement for High-Definition Television (HDTV) image. Then we study the performance of SIFT on a 64-core CMP simulator. The results show that for HDTV image, SIFT can achieve an excellent speedup of 52x and run in real-time finally. Besides the parallelization and optimization work, we also conduct a detailed performance analysis for SIFT on those two platforms. We find that load imbalance significantly limits the scalability and SIFT suffers from intensive burst memory bandwidth requirement on the 16-core SMP system. However, on the 64-core CMP simulator the memory pressure is not high due to the shared last-level cache (LLC) which accommodates tremendous read-write sharing in SIFT. Thus it does not affect the scaling performance. In short, understanding the characterization of SIFT can help identify the program bottlenecks and give us further insights into designing better systems. 1

EFMVFL: An Efficient and Flexible Multi-party Vertical Federated Learning without a Third Party

Federated learning allows multiple participants to conduct joint modeling without disclosing their local data. Vertical federated learning (VFL) handles the situation where participants share the same ID space and different feature spaces. In most VFL frameworks, to protect the security and privacy of the participants' local data, a third party is needed to generate homomorphic encryption key pairs and perform decryption operations. In this way, the third party is granted the right to decrypt information related to model parameters. However, it isn't easy to find such a credible entity in the real world. Existing methods for solving this problem are either communication-intensive or unsuitable for multi-party scenarios. By combining secret sharing and homomorphic encryption, we propose a novel VFL framework without a third party called EFMVFL, which supports flexible expansion to multiple participants with low communication overhead and is applicable to generalized linear models. We give instantiations of our framework under logistic regression and Poisson regression. Theoretical analysis and experiments show that our framework is secure, more efficient, and easy to be extended to multiple participants.Comment: 9pages,2 figure

Combined Effect of Healthy Lifestyle Factors and Risks of Colorectal Adenoma, Colorectal Cancer, and Colorectal Cancer Mortality: Systematic Review and Meta-Analysis

BackgroundIn addition to adiposity, lifestyle factors such as poor diet, low physical activity, alcohol intake and smoking are noted to be associated with the development of colorectal cancer (CRC). This study aims to investigate the association and dose-response relationship between adherence to a healthy lifestyle and CRC risk.MethodsA systematic literature search was conducted in MEDLINE and EMBASE for studies examining multiple lifestyle factors with risk of CRC, incident colorectal adenoma (CRA), and CRC-specific mortality through June 2021 without restrictions on language or study design. Meta-analysis was performed to pool hazard ratios using random-effects model. Subgroup analyses were performed based upon study and sample characteristics. Random-effects dose-response analysis was also conducted for CRC risk to assess the effect of each additional healthy lifestyle factor.ResultsA total of 28 studies (18 cohort studies, eight case-control studies, and two cross-sectional study) were included. When comparing subjects with the healthiest lifestyle to those with the least healthy lifestyle, the pooled HR was statistically significant for CRC (0.52, 95% CI 0.44-0.63), colon cancer (0.54, 95% CI 0.44-0.67), rectal cancer (0.51, 95% CI 0.37-0.70), CRA (0.39, 95% CI 0.29-0.53), and CRC-specific mortality (0.65, 95% CI 0.52-0.81). The pooled HR for CRC was 0.91 (95% CI: 0.88-0.94) for each increase in the number of healthy lifestyles. The inverse association between healthy lifestyle and CRC risk was consistently observed in all subgroups (HR ranging from 0.26 to 0.86).ConclusionsAdoption of a higher number of healthy lifestyles is associated with lower risk of CRC, CRA, and CRC-specific mortality. Promoting healthy lifestyle could reduce the burden of CRC.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=231398, identifier CRD42021231398

Enhanced fermentative performance under stresses of multiple lignocellulose-derived inhibitors by overexpression of a typical 2-Cys peroxiredoxin from Kluyveromyces marxianus

Additional file 1: Figure S1. Construction of overexpressing vector and subsequent verification. a) The schematic of overexpressing vector containing KmTPX1 gene and its own promoter. b) PCR and restriction enzyme digestion verification with a band of 1042 bp. c) Relative abundance of KmTPX1 overexpression in SC-His medium by real-time quantitative PCR technology

Anti-rheumatic effect of quercetin and recent developments in nano formulation

Rheumatoid arthritis (RA) is a common worldwide chronic autoimmune disease, characterised by synovial hyperplasia, inflammatory cell infiltration, pannus formation and destruction of articular cartilage and bone matrix. It is one of the most common forms of osteoarthritis bestowing high rates of both disability and death. Increasing attention has been paid to the use of natural medicines and natural products in the treatment of RA and patients' acceptance has increased year by year because of their high efficacy and safety. Flavonoids are a group of important secondary metabolites occurring in many plants which have rich biological activities such as anti-rheumatic, vasodilator, and anti-tumor effects. Many successful medical treatments of RA appear to be attributable to the application of flavonoids. Quercetin, a representative active member of the flavonoid family, is found abundantly in many plants,e.g.apples, berries, cabbages, onions, and ginkgo. In recent years, progress has been made in the research of its anti-rheumatoid effects which indicate that it is potentially a noteworthy prodrug for the treatment of RA. However, the poor solubility of quercetin affects its bioavailability and clinical efficacy. This review aims to provide an up to date summary of the biological effects and mechanism of action of quercetin for the treatment of RA, and the research progress made towards nano formulations of quercetin to improve its solubility and efficacy