National Supercomputing Center Research Articles

MST: Topology-Aware Message Aggregation for Exascale Graph Processing of Traversal-Centric Algorithms

This paper presents MST, a communication-efficient message library for fast graph traversal on exascale clusters. The key idea is to follow the multi-level network topology to perform topology-aware message aggregation, where small messages are gathered and scattered at each level of domain. To facilitate message aggregation, we equip MST with flexible buffer management including active buffer switching and dynamic buffer expansion. We implement MST on the newest-generation Tianhe supercomputer and evaluated its performance using various traversal-centric algorithms on both synthetic trillion-scale graphs and real-world big graphs. The results show that MST-based graph traversal is orders of magnitude faster than that based on Active Messages Library (AML). For the Graph500-BFS benchmark, MST-based Tianhe (with 77.2K nodes) outperforms the Fugaku supercomputer (with 148.5K nodes) by 18.53%, while Fugaku is ranked No. 1 in the latest Graph500-BFS ranking (June 2023). MST also greatly improves graph processing performance on other commercial large-scale computing systems at the National Supercomputing Center in Changsha (NSCC) and WuzhenLight.

The impact of surging computing power on enterprise digital transformation–Based on quasi-natural experiments set up by the National Supercomputing Center

This paper meticulously scrutinize the ramifications of the surge in computing power on enterprises' digital transformation endeavors.Our investigation reveals that the surge in computing power has a profound and statistically robust influence on enhancing the extent of enterprise digital transformation. Our findings highlight two critical conduits for fostering enterprise digital transformation: augmenting R&D investments and magnifying the marginal returns on capital. The catalytic effect of the computing power surges on enterprise digital transformation primarily resonates with companies boasting a high level of trust from their shareholders and operating within traditional industries.

Does large-scale research infrastructure affect regional knowledge innovation, and how? A case study of the National Supercomputing Center in China

Large-scale research infrastructures (LSRIs) are widely acknowledged as a crucial instrument for venturing into the uncharted territories of science and technology, as well as contributing to the well-being of society. However, only a limited number of literature have scrutinized the impact of LSRIs, founded upon a causal inference framework. Moreover, the function of LSRIs in the advancement of innovation at the regional level remains inadequately identified. Drawing on the resource-based view, this study develops a conceptual framework that links the scientific effect of LSRIs to innovation resources in order to assess their impact on knowledge innovation (KI). Taking China’s National Supercomputing Center (NSC) as a case, three major mechanism hypotheses are proposed for the impact of NSC on KI, including basic effect, network effect, and technology effect. Using panel data from 283 cities in China from 2000 to 2020, we employ a spatial difference-in-differences estimation model to examine the impact of NSC on KI. The research finds that: (1) The construction of NSC stimulates KI in local and surrounding areas. (2) The main mechanisms by which NSC promotes KI include the increase in fiscal investment and talents in science, the improvement of digital infrastructure, as well as the enhancement of urban network centrality and innovation efficiency. (3) Geographical proximity, cooperation proximity, and digitization proximity constitute the main channels of policy spillover. (4) NSC has not shown significant promotion of regional innovation convergence, and its radiation influence needs further improvement. (5) The knowledge innovation effects of NSCs manifest heterogeneity based on the distinct knowledge orientation and innovation environment, with this impact being notably pronounced in application innovation-oriented cities such as Shenzhen. The results of this study reveal the positive yet limited impact of NSC on KI and provide a reference for other economies in the areas of LSRIs, digital infrastructure, and the formulation of place-based innovation policy.

High Energy Consumption or Dirty Energy Using? The Driving Factors Behind Carbon Emission in National Supercomputing Centers

High Energy Consumption or Dirty Energy Using? The Driving Factors Behind Carbon Emission in National Supercomputing Centers

The impact of computing infrastructure on carbon emissions: an empirical study based on china national supercomputing center

Digitalization is viewed as a potential solution to environmental sustainability issues. However, existing researches suggest that the environmental impact of digital technology is uncertain. This study focuses on the National Supercomputing Center (NSC) in China, a large-scale computing infrastructure, and expands the correlation between digital infrastructure and green development from a computing perspective. Based on the synthetic control method, we select non-supercomputing cities as the control group and assign appropriate weighting. Through the fitting of a synthetic control group (refer to as the synthetic city) with similar characteristics, the analysis is conducted to compare carbon emissions (CO2 emission) between NSC city and the synthetic city. The empirical results show that the NSC may worsen regional CO2 emissions, and this result still holds true after a series of robustness tests. Mechanism examinations show that the NSC does not exhibit significant composition effect (energy structure improvement) and technology effect (green technology innovation), while scale effect (increase in energy demand and consumption) dominate the NSC’s carbon emissions. Based on these findings, we consider that in addition to improving the energy efficiency of supercomputing centers, the adoption of cleaner renewable energy and the promotion of knowledge spillovers are crucial for achieving a green transformation for computing infrastructure.

Pinpointing atrial fibrillation drivers by informed sequential endocardial mapping in the presence and absence of fibrosis: an in-silico study

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): This work is part of Personalize AF. This project received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860974. This work was also supported by the Swiss National Supercomputing Centre (CSCS), project s1074. Background We recently developed a novel technique to localize spatially stable atrial fibrillation (AF) drivers using the combined information from sequential endocardial mapping recordings. The robustness of this technique to localize drivers in the presence of complex substrate with a high degree of fibrosis and with unstable and meandering drivers is not known. Purpose To evaluate the effect of spatial instability of drivers and high AF substrate complexity caused by atrial fibrosis on the performance of the recently developed technique for AF driver localisation using sequential endocardial mapping. Methods We used a previously validated volumetric 3D atrial model to simulate AF initiated by incremental pacing. Two sets of simulation were generated, with no structural changes (n=7), and with severe remodelling (n=11), implemented as patches of endomysial fibrosis covering 70% of the atria. Simulated endocardial unipolar electrograms were generated sequentially in a 4x4 electrode grid (3 mm spacing, 2.5 s) starting from 20 uniformly spaced positions in the atria. The subsequent catheter positions were determined by analysing the propagation direction in the grid. If the measured activity was repetitive, the dominant direction of propagation was determined, and the catheter was repositioned 10 mm upstream within the same atrium. Otherwise, the catheter was moved 5 mm in a random direction. This procedure continued until either 1) a driver (re-entry or radial spread of activations) was detected directly at the recorded region by evaluating the corresponding propagation patterns, or 2) the previous catheter positions defined an enclosed region in the atrium, encircling the AF driver. The performance of the algorithm was compared between the two remodelling stages with respect to number of steps required to locate a driver, and to the distance to the closest driver. Results In the simulations with fibrosis more drivers were present than in the simulations without fibrosis (4 [2, 6] vs. 3 [2; 4] simultaneous reentries, p < 0.001). Drivers were spatially unstable and meandered substantially through the atrium. The performance of the algorithm to localize the drivers was similar in both groups. The tracking procedures located a driver after 6 [IQR: 4; 9] vs. 5 [3; 8] steps (p<0.01). The algorithm localized the driver correctly in 72.8% vs. 78.2% (p = 0.30) of the cases and the final distances to a driver were 7.87 [5.88; 11.04] mm and 7.78 [5.55, 11.35] mm (p=0.95), respectively. More drivers were detected by encircling them with sequential catheter positions in the cases without remodelling (62.6% vs. 40.9%, p<0.001). Conclusion Guiding mapping catheters by functional aspects of AF and combining sequential recordings may increase the efficiency and accuracy of mapping procedures. The developed algorithm successfully localizes AF drivers even in complex substrates for AF.

Detection of the most dominant drivers of atrial fibrillation based on repetitive activity in sequential electro-anatomical mapping

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): This work is part of Personalize AF. This project received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860974, This work was also supported by the Swiss National Supercomputing Centre (CSCS), project s1074. Introduction Detecting and targeting the most dominant drivers of atrial fibrillation (AF) might improve the outcome of AF ablation procedures. We hypothesize that dominant drivers entrain their vicinity in a temporally and spatially stable manner resulting in local as well as adjacent repetitive activation patterns. Purpose We present a novel approach to detect the most dominant drivers of AF based on driver repetitiveness and the degree to which they entrain their vicinity. Methods We retrospectively analyzed a dataset of high-density bi-atrial sequential mapping in ablation-naive persistent AF patients (n=13, 30s recording per site). Candidate drivers (focal activity or re-entry) were detected based on local activation time analysis of unipolar electrograms. Focal activity was defined as radial spread of activation, re-entry as a circular activation sequence on at least 4 splines of the mapping catheter that covered >50% of the AF cycle length. As a measure of driver stability, we determined the driver's local repetitiveness (in % of recording). As a measure of driver-associated entrainment, we determined the directionally coherent repetitiveness of adjacent recordings within 30 mm (Figure 1). Following our hypothesis, most dominant drivers can be recognized by their high local and directional coherent adjacent repetitiveness. Results A total of 459 recordings were analyzed (35±5 per patient). We detected 130 focal activities (10±3 per patient) and 42 re-entries (4±2 per patient) in total. The spatial distribution of all drivers is shown in Figure 2 (blue bars). Focal activities were more repetitive than re-entries (Figure 2, median [IQR] 3.2% [1.9%, 5.6%] vs. 1.8% [1.8%, 2.2%], p<0.001 Mann-Whitney U-test). When applying a 90th percentile threshold (8.2%) to both the local and directional coherent adjacent repetitiveness to detect the most dominant drivers, we were able to detect 9 dominant drivers (all focal activities, 7 patients). Most dominant drivers were located in the upper right atrium or left pulmonary vein region (Figure 2). Interestingly, only 9 of the 130 initially detected drivers (7%) showed an activation pattern in line with a repetitive entrainment of their vicinity. Furthermore, in 6 patients (46%), no dominant drivers were detected. This might indicate that not all patients have temporally and spatially stable drivers. Conclusion In this abstract we present a novel methodology to detect the most dominant drivers of AF. Using this method, we found that some (but not all) patients have temporally and spatially stable drivers that are able to entrain their vicinity.

PASC23 Scales to New Heights, June 26--28

The Platform for Advanced Scientific Computing (PASC) Conference, co-sponsored by SIGHPC and the Swiss National Supercomputing Centre (CSCS), takes place from June 26 to 28, 2023 at the Congress Center Davos, located in Davos, Switzerland. This year's theme is Computing Across Scales, Domains, and Communities.

Versatile software-defined HPC and cloud clusters on Alps supercomputer for diverse workflows

Supercomputers have been driving innovations for performance and scaling benefiting several scientific applications for the past few decades. Yet their ecosystems remain virtually unchanged when it comes to integrating distributed data-driven workflows, primarily due to rather rigid access methods and restricted configuration management options. X-as-a-Service model of cloud has introduced, among other features, a developer-centric DevOps approach empowering developers of infrastructure, platform to software artefacts, which, unfortunately contemporary supercomputers still lack. We introduce vClusters (versatile software-defined clusters), which is based on Infrastructure-as-code (IaC) technology. vClusters approach is a unique fusion of HPC and cloud technologies resulting in a software-defined, multi-tenant cluster on a supercomputing ecosystem, that, together with software-defined storage, enable DevOps for complex, data-driven workflows like grid middleware, alongside a classic HPC platform. IaC has been a commonplace in cloud computing, however, it lacked adoption within multi-Petascale ecosystems due to concerns related to performance and interoperability with classic HPC data centres’ ecosystems. We present an overview of the Swiss National Supercomputing Centre’s flagship Alps ecosystem as an implementation target for vClusters for HPC and data-driven workflows. Alps is based on the Cray-HPE Shasta EX supercomputing platform that includes an IaC compliant, microservices architecture (MSA) management system, which we leverage for demonstrating vClusters usage for our diverse operational workflows. We provide implementation details of two operational vClusters platforms: a classic HPC platform that is used predominantly by hundreds of users running thousands of large-scale numerical simulations batch jobs; and a widely used, data-intensive, Grid computing middleware platform used for CERN Worldwide LHC Computing Grid (WLCG) operations. The resulting solution showcases reuse and reduction of common configuration recipes across vCluster implementations, minimising operational change management overheads while introducing flexibility for managing artefacts for DevOps required by diverse workflows.

Long-term demographic forecasting

The results of the latest demographic forecasts from the world’s leading specialized centers (United Nations Population Division, the Wittgenstein Center for Demography and Global Human Capital, the Institute for Health Metrics and Evaluation) are considered, demonstrating a certain bias in favor of individual countries and their calculation methods. The second part of this article provides a description of a digital twin of the planet’s demographic system constructed by a Chinese−Russian team and implemented in China’s national supercomputer center. In addition, the results of some calculations carried out using this tool are described.

The ICON-A model for direct QBO simulations on GPUs (version icon-cscs:baf28a514)

Abstract. Classical numerical models for the global atmosphere, as used for numerical weather forecasting or climate research, have been developed for conventional central processing unit (CPU) architectures. This hinders the employment of such models on current top-performing supercomputers, which achieve their computing power with hybrid architectures, mostly using graphics processing units (GPUs). Thus also scientific applications of such models are restricted to the lesser computer power of CPUs. Here we present the development of a GPU-enabled version of the ICON atmosphere model (ICON-A), motivated by a research project on the quasi-biennial oscillation (QBO), a global-scale wind oscillation in the equatorial stratosphere that depends on a broad spectrum of atmospheric waves, which originates from tropical deep convection. Resolving the relevant scales, from a few kilometers to the size of the globe, is a formidable computational problem, which can only be realized now on top-performing supercomputers. This motivated porting ICON-A, in the specific configuration needed for the research project, in a first step to the GPU architecture of the Piz Daint computer at the Swiss National Supercomputing Centre and in a second step to the JUWELS Booster computer at the Forschungszentrum Jülich. On Piz Daint, the ported code achieves a single-node GPU vs. CPU speedup factor of 6.4 and allows for global experiments at a horizontal resolution of 5 km on 1024 computing nodes with 1 GPU per node with a turnover of 48 simulated days per day. On JUWELS Booster, the more modern hardware in combination with an upgraded code base allows for simulations at the same resolution on 128 computing nodes with 4 GPUs per node and a turnover of 133 simulated days per day. Additionally, the code still remains functional on CPUs, as is demonstrated by additional experiments on the Levante compute system at the German Climate Computing Center. While the application shows good weak scaling over the tested 16-fold increase in grid size and node count, making also higher resolved global simulations possible, the strong scaling on GPUs is relatively poor, which limits the options to increase turnover with more nodes. Initial experiments demonstrate that the ICON-A model can simulate downward-propagating QBO jets, which are driven by wave–mean flow interaction.

High‐performance computing of 3D blasting wave propagation in underground rock cavern by using 4D‐LSM on TianHe‐3 prototype E class supercomputer

AbstractParallel computing assigns the computing model to different processors on different devices and implements it simultaneously. Accordingly, it has broad applications in the numerical simulation of geotechnical engineering and underground engineering, of which models are always large‐scale. With parallel computing, the computing time or the memory requirements will be reduced by splitting the original domain of the numerical model into many subdomains, which is thus named as the domain decomposition method. In this study, a cubic and equal volume domain decomposition strategy was utilized to realize the parallel computing on the distributed memory system of four‐dimensional lattice spring model (4D‐LSM) based on the message passing interface. With a more efficient communication strategy introduced, this study aimed at operating an one‐billion‐particle model on a supercomputer platform. The preprocessing procedure of the parallelized 4D‐LSM was restructured and the particle generation strategy suitable for the supercomputer platform was employed to minimize the time consumption in preprocessing and calculation. On this basis, numerical calculations were performed on TianHe‐3 prototype E class supercomputer at the National Supercomputer Center in Tianjin. Two field‐scale three‐dimensional blasting wave propagation models were carried out, of which the numerical results verify the computing power and the advantage of the parallelized 4D‐LSM in the simulation of large‐scale three‐dimension models. Subsequently, the time complexity and spatial complexity of 4D‐LSM and other particle discrete element methods were analyzed.

Discovery of new characterizations of parameter distributions in a semi- empirical mass model: an investigation by dividing an overdetermined system into numerous balanced subsystems* *Supported by the National Natural Science Foundation of China (11975209, U2032211, 12075287), the Physics Research and Development Program of Zhengzhou University (32410017), the Project of Youth Backbone Teachers of Colleges and Universities of Henan Province (2017GGJS008)

We propose and test a new method of estimating the model parameters of the phenomenological Bethe-Weizsäcker mass formula. Based on the Monte Carlo sampling of a large dataset, we obtain, for the first time, a Cauchy-type parameter distribution formed by the exact solutions of linear equation systems. Using the maximum likelihood estimation, the location and scale parameters are evaluated. The estimated results are compared with those obtained by solving overdetermined systems, e.g., the solutions of the traditional least-squares method. Parameter correlations and uncertainty propagation are briefly discussed. As expected, it is also found that improvements in theoretical modeling (e.g., considering microscopic corrections) decrease the parameter and propagation uncertainties.

Air Stable Chalcogen-Doped Rubicenes with Diradical Character

Air Stable Chalcogen-Doped Rubicenes with Diradical Character

Distributed Tip Decomposition on Large Bipartite Graphs

Tip decomposition has a pivotal role in mining cohesive subgraphs in bipartite graphs. It is a popular research topic with wide applications in document clustering, spam group detection, and analysis of affiliation networks. With the explosive growth of the bipartite graph data scale in these scenarios, it is necessary to use distributed methods to realize its effective storage. For this reason, this paper studies the problem of the tip decomposition on a bipartite graph in the distributed environment for the first time. Firstly, a new relay-based communication mode is proposed to realize effective message transmission when the given bipartite graph is decomposed in a distributed environment. Secondly, the Distributed Butterfly Counting (DBC) algorithm and the Distributed Tip Decomposition (DTD) algorithm are designed. In particular, a controllable parallel vertex activation strategy is proposed to solve the problem of memory overflow when DBC decomposes large-scale bipartite graphs. Finally, the message pruning strategy based on vertex priority and message validity pruning strategy are introduced to further improve the efficiency of the algorithm by reducing redundant communication and computing overhead. The experiment is deployed on the high-performance distributed computing platform of the National Supercomputing Center. The effectiveness and efficiency of the proposed algorithms are verified by experiments on several real datasets.

A Packet Loss Monitoring System for In-Band Network Telemetry: Detection, Localization, Diagnosis and Recovery

Network measurement provides rich data for network monitoring, control, and management. In-band network telemetry (INT) is a new network measurement technology that uses normal data packet to collect network information hop-by-hop. However, the design and implementation of INT protocol cannot do anything about packet loss: (1) The end-to-end telemetry mechanism makes INT unable to detect packet loss; (2) Since data packets may be lost due to various reasons, INT telemetry information will inevitably be lost. In summary, INT system by itself is unreliable. Incomplete telemetry data will seriously affect the performance of upper-layer network telemetry applications. In this paper, we present our successful experience in INT packet loss monitoring. We design, implement, and open source a powerful packet loss monitoring system for INT, called LossSight. The functions of LossSight include the detection of packet loss events, the deduction of the time and location of the losses, the diagnose of the root cause of the losses, and the recovery of the lost INT information. Experiment results show that LossSight provides excellent performance and extremely low overhead, including detection accuracy and diagnostic precision close to 100%, and detection latency of just milliseconds. In particular, LossSight uses a generative adversarial network to recover lost telemetry information, with excellent accuracy and reliability. LossSight has been running stably in the supercomputing interconnection environment of the National Supercomputing Center in Jinan. We suggest that all INT applications that require reliable telemetry information should be implemented based on LossSight.

Color halo scenario of charmonium-like hybrids * *Supported by the National Key Research and Development Program of China (2017YFB0203202), the Strategic Priority Research Program of Chinese Academy of Sciences (XDB34030302, XDC01040100), the National Natural Science Foundation of China (11935017, 11575196, 11775229, 12075253, 12070131001) (CRC 110 by DFG and NSFC). The numerical calculations are carried out on Tianhe-1A at the National

The internal structures of charmonium-like hybrids are investigated under lattice QCD in the quenched approximation. We define the Bethe-Salpeter wave function ( ) in the Coulomb gauge as the matrix element of a spatially extended hybrid-like operator ( ) between the vacuum and n-th state for each , with r being the spatial separation between a localized component and the chromomagnetic strength tensor. These wave functions exhibit some similarities for states with the aforementioned different quantum numbers, and their r-behaviors (no node for the ground states and one node for the first excited states) imply that r can be a meaningful dynamical variable for these states. Additionally, the mass splittings of the ground states and first excited states of charmonium-like hybrids in these channels are obtained for the first time to be approximately 1.2-1.4 GeV. These results do not support the flux-tube description of heavy-quarkonium-like hybrids in the Born-Oppenheimer approximation. In contrast, a charmonium-like hybrid can be viewed as a “color halo” charmonium for which a relatively localized color octet is surrounded by gluonic degrees of freedom, which can readily decay into a charmonium state along with one or more light hadrons. The color halo picture is compatible with the decay properties of and suggests LHCb and BelleII to search for charmonium-like hybrids in and final states.

Density functional theory study of formaldehyde adsorption and decomposition on Co-doped defective CeO2 (110) surface* *Project supported by the National Key Research and Development Program of China (Grant Nos. 2018YFB0704300 and 2016YFB0700500). The work was carried out at the National Supercomputer Center in Tianjin, and the calculations were performed on TianHe-1(A). This work was supported by Guangdong Provincial Key Laboratory

Formaldehyde as an air pollutant to adverse health effects for humanity has been getting attention. The adsorption and dissociation of formaldehyde (HCHO) on the Co x Ce1 – x O2 – δ (110) surface were investigated by the density functional theory (DFT) calculations. We calculated the oxygen vacancy formation energy as the function of its site around dopant Co in detail. The results showed that Co doping was accompanied by compensating oxygen hole spontaneous formation. The adsorption configurations and bindings of HCHO at different locations on the Co x Ce1 – x O2 (110) were presented. Four possible pathways of oxidation of formaldehyde on the catalytic surface were explored. The results suggested that formaldehyde dissociation at different adsorption sites on the doped CeO2 (110) — first forming dioxymethylene (CH2O2) intermediate, and then decomposing into H2O, H2, CO2, and CO molecules. It was found that the presence of cobalt and oxygen vacancy significantly prompted the surface activity of CeO2.

Electrochemical Aziridination of Tetrasubstituted Alkenes with Ammonia

Ammonia (NH3) is an ideal nitrogen source in terms of availability, reactivity, safety, atom economy, environmental compatibility, and ease of isolation. However, its utility for amine synthesis is...

NBN-doped nanographene embedded with five- and seven-membered rings on Au(111) surface* *Project supported by the National Natural Science Foundation of China (Grant Nos. 51761135130 and 61888102), the National Key R&D Program of China (Grant Nos. 2018YFA0305800 and 2019YFA0308500), DFG EnhanceNano (Grant No. 391979941), the Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDB30000000), the International Partnership Program

Nanographenes (NGs) can be embedded with predesigned dopants or nonhexagonal rings to tailor the electronic properties and provide ideal platforms to study the unique physical and chemical properties. Here, we report the on-surface synthesis of NBN-doped NG embedded with five- and seven-membered rings (NBN-575-NG) on Au(111) from a oligophenylene precursor preinstalled with a NBN unit and a heptagonal ring. Scanning tunneling microscopy and non-contact atomic force microscopy images elucidate the intramolecular cyclodehydrogenation and the existence of the five- and seven-membered rings. Scanning tunneling spectroscopy spectra reveal that the NBN-575-NG is a semiconductor, which agrees with the density functional theory calculation results on a freestanding NBN-575-NG with the same structure. This work provides a feasible approach for the on-surface synthesis of novel NGs containing non-hexagonal rings.