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第190回 第1部
日時: 2020年2月3日(月)、13:00 - 13:40
場所: R-CCS 6階講堂

・講演題目:Recent advances in coarse-grained modeling of biomolecules and the implementation in GENESIS
・講演者:Cheng Tan(粒子系生物物理研究チーム)
※発表・スライド共に英語

講演要旨: 詳細を見る

Compared with all-atom force fields, early coarse-grained (CG) models were once considered as "toys" to study qualitative properties of biophsical processes such as protein folding. However, as people's interest increases in large-scale biological phenomenons, such as genome organization, liquid-liquid phase separation, and virus capsid assembly, CG models begin to show their advantage in lower computational cost. On the other hand, recent development of the CG models also gained great success in improving the accuracy. We first review the advances of the latest CG models for protein, DNA, and RNA. We then describe the currenet progress of the implementation of these models in the MD software GENESIS. At last, we show some simple applications of the CG simulations with GENESIS.

第190回 第2部
日時: 2020年2月3日(月)、13:40 - 14:20
場所: R-CCS 6階講堂

・講演題目:Simulations of dynamics in quantum many-body systems
・講演者:白川 知功(量子系物質科学研究チーム)
※発表・スライド共に英語

講演要旨: 詳細を見る

The quantum many-body systems give us a rich field which potentially yields unexpected phenomena. Especially, their dynamics have attracted much attention due to the recent progress of the experimental realizations. The striking examples are the quantum computations since both of the quantum annealing and the gate-type quantum devices can be regarded as the controlled dynamics of the quantum many-body systems. In this talk, I would like to discuss our recent studies on the dynamics for quantum many-body systems, including the photo-induced superconductivity as well as the simulations of the gate-type quantum computations.

第189回 第1部
日時: 2020年1月27日(月)、15:30 - 16:10
場所: R-CCS 6階講堂

・講演題目:Design of An FPGA-based Matrix Multiplier
・講演者:Tan Yiyu(大規模並列数値計算技術研究チーム)
※発表・スライド共に英語

講演要旨: 詳細を見る

Matrix multiplication requires computer systems have huge computing capability and data throughputs as problem size is increased. In this research, an OpenCL-based matrix multiplier with task parallelism is designed and implemented by using the FPGA board DE5a-NET to improve computation throughput and energy efficiency. The matrix multiplier is based on the systolic array architecture with 10 × 16 processing elements (PEs). When data are single-precision floating-point, the proposed matrix multiplier averagely achieves about 785 GFLOPs in computation throughput and 66.75 GFLOPs/W in energy efficiency. Compared with the Intel’s OpenCL example with data parallelism on FPGA, the SGEMM routines in the Intel MKL and OpenBLAS libraries executed on a desktop with 32 GB DDR4 RAMs and an Intel i7-6800K processor running at 3.4 GHz, the proposed matrix multiplier averagely outperforms by 3.2 times, 1.3 times, and 1.6 times in omputation throughput, and by 2.9 times, 10.5 times, and 11.8 times in energy efficiency, respectively, even though the fabrication technology is 20 nm in the FPGA while it is 14 nm in the CPU.

第189回 第2部
日時: 2020年1月27日(月)、16:10 - 16:50
場所: R-CCS 6階講堂

・講演題目:Multi-Scale Simulation to Predict Biodegradability of Plastics
・講演者:川嶋 英佑(量子系分子科学研究チーム)
※発表・スライド共に英語

講演要旨: 詳細を見る

Biodegradable plastics are attracting attention to reduce environmental impact and achieve Sustainable Development Goals, SDGs. We, the computational molecular science research team, are developing theoretical tools to estimate biodegradability of plastics to offer design guideline, by applying materials informatics. I will talk about multi-scale simulators of biodegradation. Changes of molecular weight distributions under degradation are estimated by a macroscopic Monte Carlo simulation. Hydrolysis reaction pathways of polyesters are investigated by nudged elastic band, NEB, as implemented in NTChem, a quantum chemistry package developed by us, and activation energies and heats of reaction are obtained. We are developing models to predict these values from monomer structures.

第188回 第1部
日時: 2020年1月14日(火)、13:00 - 13:40
場所: R-CCS 6階講堂

・講演題目:Traffic simulation and models
・講演者:伊藤 伸泰(離散事象シミュレーション研究チーム、チームリーダー)
※発表・スライド共に英語

講演要旨: 詳細を見る

Simple model is expected to make reliable simulations, but it is not always available for social phenomena and complicated adhoc models are often used. Traffic simulation is an example. Various models are proposed and used for traffic phenomena, In this talk, traffic phenomena and their models are briefly reviewed.

第188回 第2部
日時: 2020年1月14日(火)、13:40 - 14:20
場所: R-CCS 6階講堂

・講演題目:Performance Improvement by Domain Specific Architectures: A Case Study in Graph Processing
・講演者:近藤 正章(次世代高性能アーキテクチャ研究チーム、チームリーダー)
※発表・スライド共に英語

講演要旨: 詳細を見る

The continuous improvement in processing speed in high-performance computer systems has been enabled by transistor scaling known as Moore's law. However, this trend is predicted to end in the near future. It is vital to research and develop new, more efficient high performance architectures to continue realizing high performance computing systems. One of the ways to improve performance of computer systems in the post-Moore era is utilizing domain specific architectures. In this talk, we briefly introduce our recent research efforts on a domain specific architecture for graph processing. In this research, we focus on the edge-centric graph processing model and propose a dedicated cache architecture for exploiting data locality. We have evaluated our cache architecture by a light weight cache simulation and the results showed that it can reduce the number of LLC cache misses by up to 89.9%.

第187回 第1部
日時: 2019年12月16日(月)、15:30 - 16:10
場所: R-CCS 6階講堂

・講演題目:Scalable fixed-mesh method for simulations of multi-material vehicle structures
・講演者:西口 浩司(複雑現象統一的解法研究チーム)
※発表・スライド共に英語

講演要旨: 詳細を見る

In recent years, in the automotive industry, weight reductions are indispensable for complying with carbon dioxide emission regulations. Although automotive companies have been mainly using steel sheets, they want to employ multi-material structures including extrusions, castings, or 3D printings of aluminum alloy or resin to achieve weight reductions. However, the structural design will be more complex because multi-material structures have a higher degree of geometric freedom than sheet metal structures. Therefore, numerical simulations need to play a more critical role in designing optimal vehicle structures.
For the last several decades, a Lagrangian finite element method (FEM) using mainly shell formulation has been the de facto standard in the automotive industry. However, shell formulation cannot numerically model the multi-material structures mentioned above because they do not have a constant thickness. Thus, the continuum formulation has to be applied, but this approach poses two computational problems.
The first problem is that an enormous number of finite elements using continuum formulation is required to discretize the multi-material structures spatially. A scalable method in a massively parallel environment is indispensable for this simulation. Secondly, we need to spend more than a month to generate the finite element mesh of a car body. Therefore, it is challenging to investigate many patterns of vehicle structures.
Considering the background as mentioned above, we focus on a Eulerian finite volume method (FVM) [1] based on continuum formulation [2] using a scalable hierarchical Cartesian mesh method [1]. This Eulerian FVM [1] has the following three advantages. The first one is good scalability [1] in a massively parallel computing environment. Secondly, we can easily generate the computational mesh of a car body only within 10 minutes. We will demonstrate the stiffness analysis of a body-in-white structure, which is spatially discretized by approximately 200 million cells and was computed using 104,520 cores on the K computer. Thirdly, the proposed Eulerian method is easy to couple a conventional finite volume fluid solver.
In future work, we plan to conduct car crash simulations using many patterns of multi-material vehicle structures to study ultralight vehicle structures.
[1] K. Nishiguchi 2019 https://doi.org/10.1002/nme.5954 [2] K. Nishiguchi 2018 https://doi.org/10.1002/nme.5790

第187回 第2部
日時: 2019年12月16日(月)、16:10 - 16:50
場所: R-CCS 6階講堂

・講演題目:System Software for Emerging Hardware Technologies in Computing Systems
・講演者:小柴 篤史(プロセッサ研究チーム)
※発表・スライド共に英語

講演要旨: 詳細を見る

In this talk, I will introduce some of my previous work including my Ph.D. thesis, new OS features and middleware to make use of emerging hardware technologies. Emerging hardware devices/features (e.g., FPGA/ASICs, non-volatile memories, Intel SGX) have been widely studied due to strong demands on performance improvement, energy efficiency, and data protection of computer systems. However, due to a lack of system software support, existing computer systems cannot fully utilize these new devices. I have proposed new operating system functions and middleware, which are useful to improve the performance/usability of the devices or analyze an application behavior with them.

第186回
日時: 2019年12月10日(火)、10:00 - 11:00
場所: R-CCS 1階セミナー室

・講演題目:Next generation optics/photonics broadens system architecture aperture
・講演者:Dube, Nicolas (Dr. / Chief Strategist for High-Performance Computing at Hewlett Packard Enterprise)
※発表・スライド共に英語

講演要旨: 詳細を見る

This presentation will introduce new optical devices that enable HPC and AI system architectures to free up from cost-prohibitive active optical cables and scale-limiting copper cables. Developed by parallel teams at HPE, VCSEL based and silicon photonics ring resonator technologies both enable passive optics at scale, and can integrate as mid-board, co-packaged or even 3D-stacked optical devices. These technologies set the course for much more capable interconnects, thanks to a significantly reduced cost structure and an energy profile tracking to sub 10 pJ/bit. Application at the system level will then be outlined, including the enablement of the Hyper-X and other multi-dimensional all to all topologies thanks to new components like fiber-shuffles.

第185回 第1部
日時: 2019年12月2日(月)、13:00 - 13:40
場所: R-CCS 6階講堂

・講演題目:Parallel Multigrid Methods on Manycore Clusters with IHK/McKernel
・講演者:中島 研吾(計算科学研究センター 副センター長)
※発表・スライド共に英語
(BlueJeansによる遠隔セミナーとなります)

講演要旨: 詳細を見る

The parallel multigrid method is expected to play an important role in large-scale scientific computing on exa-scale supercomputer systems. Previously we proposed Hierarchical Coarse Grid Aggregation (hCGA), which dramatically improved the performance of the parallel multigrid solver when the number of MPI processes was O(10^4) or more. Because hCGA can handle only two layers of parallel hierarchical levels, the computation overhead due to coarse grid solver may become significant when the number of MPI processes reaches O(10^5)- O(10^6) or more. In the present work, we propose AM-hCGA (Adaptive Multilevel hCGA) that can take into account multiple layers of three or more levels, and show preliminary results using the Oakforest-PACS (OFP) system by JCAHPC. Additionally, we also examine the impact of a lightweight multi-kernel operating system, called IHK/McKernel, for parallel multigrid solvers running on OFP.

This is a joint work with Balazs Gerofi (RIKEN R-CCS), Yutaka Ishikawa (RIKEN R-CCS), and Masashi Horikoshi (Intel).