Exploring Scientific Application Performance Using Large Scale Object Storage

One of the major performance and scalability bottlenecks in large scientific applications is parallel reading and writing to supercomputer I/O systems. The usage of parallel file systems and consistency requirements of POSIX, that all the traditional HPC parallel I/O interfaces adhere to, pose limitations to the scalability of scientific applications. Object storage is a widely used storage technology in cloud computing and is more frequently proposed for HPC workload to address and improve the current scalability and performance of I/O in scientific applications. While object storage is a promising technology, it is still unclear how scientific applications will use object storage and what the main performance benefits will be. This work addresses these questions, by emulating an object storage used by a traditional scientific application and evaluating potential performance benefits. We show that scientific applications can benefit from the usage of object storage on large scales.Comment: Preprint submitted to WOPSSS workshop at ISC 201

Examining Students’ Perceptions of Helpfulness from Asynchronous Supplemental Video Modules in a Hybrid Technology Course

Summary: While ASVMs are a common pedagogical instrument used to extend learning beyond the classroom, it is unclear how helpful students perceive these to be. Analyzing these perceptions and relating them to the quantity of ASVMs watched by students can clarify the impact of this type of course content. Ultimately, this information can be used to determine the value of investing in the development of ASVMs for a course to increase student learning, satisfaction, and achievement

Which Design and Biomaterial Factors Affect Clinical Wear Performance of Total Disc Replacements? A Systematic Review

Background Total disc replacement was clinically introduced to reduce pain and preserve segmental motion of the lumbar and cervical spine. Previous case studies have reported on the wear and adverse local tissue reactions around artificial prostheses, but it is unclear how design and biomaterials affect clinical outcomes. Questions/purposes Which design and material factors are associated with differences in clinical wear performance (implant wear and periprosthetic tissue response) of (1) lumbar and (2) cervical total disc replacements? Methods We performed a systematic review on the topics of implant wear and periprosthetic tissue response using an advanced search in MEDLINE and Scopus electronic databases. Of the 340 references identified, 33 were retrieved for full-text evaluation, from which 16 papers met the inclusion criteria (12 on lumbar disc replacement and five on cervical disc replacement; one of the included studies reported on both lumbar and cervical disc replacement), which involved semiquantitative analysis of wear and adverse local tissue reactions along with a description of the device used. An additional three papers were located by searching bibliographies of key articles. There were seven case reports, three case series, two case-control studies, and seven analytical studies. The Methodological Index for Non-randomized Studies (MINORS) Scale was used to score case series and case-control studies, which yielded mean scores of 10.3 of 16 and 17.5 of 24, respectively. In general, the case series (three) and case-control (two) studies were of good quality. Results In lumbar regions, metal-on-polymer devices with mobile-bearing designs consistently generated small and large polymeric wear debris, triggering periprosthetic tissue activation of macrophages and giant cells, respectively. In the cervical regions, metal-on-polymer devices with fixed-bearing designs had similar outcomes. All metal-on-metal constructs tended to generate small metallic wear debris, which typically triggered an adaptive immune response of predominantly activated lymphocytes. There were no retrieval studies on one-piece prostheses. Conclusions This review provides evidence that design and biomaterials affect the type of wear and inflammation. However, clinical study design, followup, and analytical techniques differ among investigations, preventing us from drawing firm conclusions about the relationship between implant design and wear performance for both cervical and lumbar total disc replacement

Characterizing Deep-Learning I/O Workloads in TensorFlow

The performance of Deep-Learning (DL) computing frameworks rely on the performance of data ingestion and checkpointing. In fact, during the training, a considerable high number of relatively small files are first loaded and pre-processed on CPUs and then moved to accelerator for computation. In addition, checkpointing and restart operations are carried out to allow DL computing frameworks to restart quickly from a checkpoint. Because of this, I/O affects the performance of DL applications. In this work, we characterize the I/O performance and scaling of TensorFlow, an open-source programming framework developed by Google and specifically designed for solving DL problems. To measure TensorFlow I/O performance, we first design a micro-benchmark to measure TensorFlow reads, and then use a TensorFlow mini-application based on AlexNet to measure the performance cost of I/O and checkpointing in TensorFlow. To improve the checkpointing performance, we design and implement a burst buffer. We find that increasing the number of threads increases TensorFlow bandwidth by a maximum of 2.3x and 7.8x on our benchmark environments. The use of the tensorFlow prefetcher results in a complete overlap of computation on accelerator and input pipeline on CPU eliminating the effective cost of I/O on the overall performance. The use of a burst buffer to checkpoint to a fast small capacity storage and copy asynchronously the checkpoints to a slower large capacity storage resulted in a performance improvement of 2.6x with respect to checkpointing directly to slower storage on our benchmark environment.Comment: Accepted for publication at pdsw-DISCS 201

Gaseous, PM2.5 Mass, and Speciated Emission Factors from Laboratory Chamber Peat Combustion

Peat fuels representing four biomes of boreal (western Russia and Siberia), temperate (northern Alaska, USA), subtropical (northern and southern Florida, USA), and tropical (Borneo, Malaysia) regions were burned in a laboratory chamber to determine gas and particle emission factors (EFs). Tests with 25 % fuel moisture were conducted with predominant smoldering combustion conditions (average modified combustion efficiency (MCE) =0.82+/-0.08). Average fuel-based EFCO2 (carbon dioxide) are highest (1400 +/- 38 g kg(-1)) and lowest (1073 +/- 63 g kg(-1)) for the Alaskan and Russian peats, respectively. EFCO (carbon monoxide) and EFCH4 (methane) are similar to 12 %15 % and similar to 0.3 %0.9 % of EFCO2, in the range of 157171 and 310 g kg(-1), respectively. EFs for nitrogen species are at the same magnitude as EFCH4, with an average of 5.6 +/- 4.8 and 4.7 +/- 3.1 g kg(-1) for EFNH3 (ammonia) and EFHCN (hydrogen cyanide); 1.9+/-1.1 g kg(-1) for EFNOx (nitrogen oxides); and 2.4+/-1.4 and 2.0 +/- 0.7 g kg(-1) for EFNOy (total reactive nitrogen) and EFN2O (nitrous oxide). An oxidation flow reactor (OFR) was used to simulate atmospheric aging times of similar to 2 and similar to 7 d to compare fresh (upstream) and aged (downstream) emissions. Filter-based EFPM2.5 varied by \u3e 4-fold (1461 g kg(-1)) without appreciable changes between fresh and aged emissions. The majority of EFPM2.5 consists of EFOC (organic carbon), with EFOC / EFPM2.5 ratios in the range of 52 %98 % for fresh emissions and similar to 14 %23 % degradation after aging. Reductions of EFOC (similar to 79 g kg(-1)) after aging are most apparent for boreal peats, with the largest degradation in low-temperature OC1 that evolves at \u3c 140 degrees C, indicating the loss of high-vapor-pressure semivolatile organic compounds upon aging. The highest EFLevoglucosan is found for Russian peat (similar to 16 g kg(-1)), with similar to 35 %50 % degradation after aging. EFs for water-soluble OC (EFWSOC) account for similar to 20 %62 % of fresh EFOC. The majority (\u3e 95 %) of the total emitted carbon is in the gas phase, with 54 %75 % CO2, followed by 8 %30 % CO. Nitrogen in the measured species explains 24 %52 % of the consumed fuel nitrogen, with an average of 35 +/- 11 %, consistent with past studies that report similar to 1/3 to 2/3 of the fuel nitrogen measured in biomass smoke. The majority (\u3e 99 %) of the total emitted nitrogen is in the gas phase, with an average of 16.7 % as NH3 and 9.5 % as HCN center dot N2O and NOy constituted 5.7 % and 2.9 % of consumed fuel nitrogen. EFs from this study can be used to refine current emission inventories

Changes in PM2.5 Peat Combustion Source Profiles with Atmospheric Aging in an Oxidation Flow Reactor

Smoke from laboratory chamber burning of peat fuels from Russia, Siberia, the USA (Alaska and Florida), and Malaysia representing boreal, temperate, subtropical, and tropical regions was sampled before and after passing through a potential-aerosol-mass oxidation flow reactor (PAM-OFR) to simulate intermediately aged (∼2 d) and well-aged (∼7 d) source profiles. Species abundances in PM2.5 between aged and fresh profiles varied by several orders of magnitude with two distinguishable clusters, centered around 0.1 % for reactive and ionic species and centered around 10 % for carbon. Organic carbon (OC) accounted for 58 %–85 % of PM2.5 mass in fresh profiles with low elemental carbon (EC) abundances (0.67 %–4.4 %). OC abundances decreased by 20 %–33 % for well-aged profiles, with reductions of 3 %–14 % for the volatile OC fractions (e.g., OC1 and OC2, thermally evolved at 140 and 280 ∘C). Ratios of organic matter (OM) to OC abundances increased by 12 %–19 % from intermediately aged to well-aged smoke. Ratios of ammonia (NH3) to PM2.5 decreased after intermediate aging. Well-aged NH+4 and NO−3 abundances increased to 7 %–8 % of PM2.5 mass, associated with decreases in NH3, low-temperature OC, and levoglucosan abundances for Siberia, Alaska, and Everglades (Florida) peats. Elevated levoglucosan was found for Russian peats, accounting for 35 %–39 % and 20 %–25 % of PM2.5 mass for fresh and aged profiles, respectively. The water-soluble organic carbon (WSOC) fractions of PM2.5 were over 2-fold higher in fresh Russian peat (37.0±2.7 %) than in Malaysian (14.6±0.9 %) peat. While Russian peat OC emissions were largely water-soluble, Malaysian peat emissions were mostly water-insoluble, with WSOC ∕ OC ratios of 0.59–0.71 and 0.18–0.40, respectively. This study shows significant differences between fresh and aged peat combustion profiles among the four biomes that can be used to establish speciated emission inventories for atmospheric modeling and receptor model source apportionment. A sufficient aging time (∼7 d) is needed to allow gas-to-particle partitioning of semi-volatilized species, gas-phase oxidation, and particle volatilization to achieve representative source profiles for regional-scale source apportionment

DECO: Liberating Web Data Using Decentralized Oracles for TLS

Thanks to the widespread deployment of TLS, users can access private data over channels with end-to-end confidentiality and integrity. What they cannot do, however, is prove to third parties the {\em provenance} of such data, i.e., that it genuinely came from a particular website. Existing approaches either introduce undesirable trust assumptions or require server-side modifications. As a result, the value of users' private data is locked up in its point of origin. Users cannot export their data with preserved integrity to other applications without help and permission from the current data holder. We propose DECO (short for \underline{dec}entralized \underline{o}racle) to address the above problems. DECO allows users to prove that a piece of data accessed via TLS came from a particular website and optionally prove statements about such data in zero-knowledge, keeping the data itself secret. DECO is the first such system that works without trusted hardware or server-side modifications. DECO can liberate data from centralized web-service silos, making it accessible to a rich spectrum of applications. To demonstrate the power of DECO, we implement three applications that are hard to achieve without it: a private financial instrument using smart contracts, converting legacy credentials to anonymous credentials, and verifiable claims against price discrimination.Comment: This is the extended version of the CCS'20 pape

Intra-tumoural lipid composition and lymphovascular invasion in breast cancer via non-invasive magnetic resonance spectroscopy

Acknowledgements The authors would like to thank Dr. Nicholas Senn for conducting data auditing, Dr. Matthew Clemence (Philips Healthcare Clinical Science, UK) for clinical scientist support, Dr. Tim Smith for biologist support, Mr. Gordon Buchan for technician support, Ms Bolanle Brikinns for patient recruitment support, Ms Dawn Younie for logistic support and Prof. Andrew M. Blamire for advice on MRS. The authors would also like to thank Mr Roger Bourne and Ms Mairi Fuller for providing access to the patients. Funding: This study has received funding from Friends of Aberdeen and North Centre for Haematology, Oncology and Radiotherapy (ANCHOR) (RS2015 004). Sai Man Cheung’s PhD study was jointly supported by Elphinstone scholarship, Roland Sutton Academic Trust and John Mallard scholarshipPeer reviewedPublisher PD