MatsuLab. Lecture Note

ハイパフォーマンスコンピューティング

日時
月曜日 10:45〜12:15(3〜4限)
場所
西8号館 832号室
連絡
松岡教授 (Prof. S.Matsuoka)matsu あっと is.
TA 金刺 (H.Kanezashi)kanezashi あっと matsulab.is.
メーリングリストに追加しますので、至急TAまでメールを送ってください。Please email to Kanezashi (TA) as soon as possible in order to add you to the mailing list.

目次

休講予定日 Lecture Cancelled

10/19, 11/16, 02/08(補講はありません We do not have supplementary lectures)

授業概要と参考資料 Guidance and References

発表スケジュール Schedule

暫定的な割り当ては以下の通りですが、都合が悪い場合はTAまで希望日をメールしてください。

禁止リスト Inhibited List

  • Training Large Scale Deep Neural Networks on the Intel Xeon Phi Many-Core Coprocessor
  • Memory fast-forward: A low cost special function unit to enhance energy efficiency in GPU for big data processing
  • Optimized Deep Learning Architectures with Fast Matrix Operation Kernels on Parallel Platform
  • Real-time anomaly detection in hyperspectral images using multivariate normal mixture models and GPU processing
  • Hyperspectral Unmixing on GPUs and Multi-Core Processors: A Comparison
  • Performance versus energy consumption of hyperspectral unmixing algorithms on multi-core platforms
  • Optimizing communication and cooling costs in HPC data centers via intelligent job allocation
  • Cost Minimization for Big Data Processing in Geo-Distributed Data Centers
  • On Characterization of Performance and Energy Efficiency in Heterogeneous HPC Cloud Data Centers
  • DaDianNao?: A Machine-Learning Supercomputer
  • Mariana: tencent deep learning platform and its applications
  • Performance Modeling and Scalability Optimization of Distributed Deep Learning Systems
  • Asynchronous parallel stochastic gradient descent: a numeric core for scalable distributed machine learning algorithms
  • FireCaffe?: near-linear acceleration of deep neural network training on compute clusters
  • CA-SVM: Communication-Avoiding Support Vector Machines on Distributed Systems
  • Large Scale Distributed Deep Networks
  • Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks
  • 24.77 Pflops on a Gravitational Tree-Code to Simulate the Milky Way Galaxy with 18600 GPUs
  • Massively Parallel Models of the Human Circulatory System
  • Moving to memoryland: in-memory computation for existing applications
  • Intelligent SSD: A Turbo for Big Data Mining
  • Scalable Multi-Access Flash Store for Big Data Analytics
  • An FPGA-Based Tightly Coupled Accelerator for Data-Intensive Applications
  • A reconfigurable fabric for accelerating large-scale datacenter services
  • An FPGA-based In-Line Accelerator for Memcached
  • Scaling Up the Training of Deep CNNs for Human Action Recognition

期末レポート Report

  • 期限 Due date: 02/17 (Extended)
  • Summarize the general topic covering and including ALL THREE PAPERS regarding the state of the art in HPC and Big Data convergence.
  • It should be 10 pages in IEEE conference paper format
  • Please submit it to TA by email (NOT mailing list)

リンク Links


添付ファイル: file06853195.pdf 342件 [詳細] fileHPC_Class_Presentation_Hamid.pdf 439件 [詳細] filefpga2014-wjun.pdf 454件 [詳細] fileHPC_kuroda.pdf 319件 [詳細] filep161-zhang-small.pdf 62802件 [詳細] fileOptimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks.pdf 2315件 [詳細] filehpc_teranishi2.pdf 409件 [詳細] fileHPC15_2015-12-14&21_Jian_FireCaffe v2.pdf 294件 [詳細] fileHPC15_2015-12-14_Jian_FireCaffe.pdf 896件 [詳細] fileFireCaffe.pdf 547件 [詳細] filehpc_teranishi.pdf 354件 [詳細] filea1-keuper.pdf 312件 [詳細] filehpc_Kanezashi1.pdf 549件 [詳細] fileDianNao.pdf 549件 [詳細] fileDaDianNao.pdf 470件 [詳細] fileHyperspectral.pdf 643件 [詳細] filehpc_uehara.pdf 495件 [詳細] fileHPC_Motoyama2.pdf 564件 [詳細] file2015年度ハイパフォーマンスコンピューティング授業内容.docx 100件 [詳細] file06735232.pdf 423件 [詳細] filehpc_Motoyama.pdf 537件 [詳細] file2015年度ハイパフォーマンスコンピューティング授業内容.pdf 1125件 [詳細]

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Last-modified: 2016-02-01 (月) 12:39:26 (655d)