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Eighth INFN International School on: "Architectures, tools and methodologies for developing efficient large scale scientific computing applications" ESC16 - Bertinoro (Forlì-Cesena) Italy 23-29 October 2016

23–29 Oct 2016
Bertinoro
Europe/Rome timezone

Contribution List

59 out of 59 displayed
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  1. 10. Welcome and introduction
    Mauro Morandin (INFN - Padova)
    24/10/2016, 09:00
  2. 11. Computer Architecture evolution and the performance challenge
    Vincenzo Innocente (CERN)
    24/10/2016, 09:30
  3. 12. Computer Architecture evolution and the performance challenge
    Vincenzo Innocente (CERN)
    24/10/2016, 11:00
  4. 13. Hands-on environment checkout
    Dr Francesco Giacomini (CNAF)
    24/10/2016, 11:45
  5. 57. Welcome by the Director of the INFN Padova site
    Mauro Mezzetto (PD)
    24/10/2016, 14:00
  6. 14. Efficient C++ programming and memory management
    Dr Francesco Giacomini (CNAF)
    24/10/2016, 14:10
  7. 15. Efficient C++ programming and memory management
    Dr Francesco Giacomini (CNAF)
    24/10/2016, 14:55
  8. 16. Efficient C++ programming and memory management
    Dr Francesco Giacomini (CNAF)
    24/10/2016, 16:10
  9. 17. Consolidation
    24/10/2016, 16:55
  10. 18. Students lightning presentations
    24/10/2016, 17:25
  11. 19. Efficient C++ programming and memory management
    Dr Francesco Giacomini (CNAF)
    25/10/2016, 08:30
  12. 20. Efficient C++ programming and memory management
    Dr Francesco Giacomini (CNAF)
    25/10/2016, 09:15
  13. 21. Efficient C++ programming and memory management
    Francesco Giacomini (CNAF)
    25/10/2016, 10:30
  14. 22. Efficient C++ programming and memory management
    Francesco Giacomini (CNAF)
    25/10/2016, 11:15
  15. 23. Consolidation
    25/10/2016, 12:00
  16. 24. Introduction to parallel computing (basic concepts)
    Dr Tim Mattson (Intel)
    25/10/2016, 15:00
  17. 25. Introduction to parallel computing with OpenMP
    Dr Tim Mattson (Intel)
    25/10/2016, 15:45
  18. 26. Parallel Performance concepts using OpenMP
    Dr Tim Mattson (Intel)
    25/10/2016, 17:00
  19. 27. Students lightning presentations
    25/10/2016, 17:45
  20. 28. Efficient C++ programming and memory management
    Francesco Giacomini (CNAF)
    26/10/2016, 08:30
  21. 29. Efficient C++ programming and memory management
    Francesco Giacomini (CNAF)
    26/10/2016, 09:15
  22. 30. A "Hands-on" introduction to OpenMP
    Dr Tim Mattson (Intel)
    26/10/2016, 10:30
  23. 31. A "Hands-on" introduction to OpenMP
    Dr Tim Mattson (Intel)
    26/10/2016, 11:15
  24. 32. Consolidation
    26/10/2016, 12:00
  25. 33. Working with OpenMP: Performance Optimization
    Dr Tim Mattson (Intel)
    26/10/2016, 14:30
  26. 34. Working with OpenMP: Debugging Applications
    Dr Tim Mattson (Intel)
    26/10/2016, 15:45
  27. 35. Consolidation
    26/10/2016, 17:00
  28. 36. Evening Lecture "Go: a different tack at building concurrent programs that grow with grace"
    Dr Sebastien Binet (LPC/IN2P3)
    26/10/2016, 18:30
    In this talk, we'll introduce the basic concepts of Go, focusing on its concurrency primitives and its interface model. We'll see how these concepts, together with a great tooling and quick edit-compile-run cycle allow for a great development environment. Finally, we'll touch on how these assets apply to science software: from control frameworks to soft real-time data acquisition systems.
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  29. 50. Efficient floating-point computation and vectorization
    Vincenzo Innocente (CERN)
    27/10/2016, 08:30
  30. 42. Efficient floating-point computation and vectorization
    Vincenzo Innocente (CERN)
    27/10/2016, 09:15
  31. 51. Efficient floating-point computation and vectorization
    Vincenzo Innocente (CERN)
    27/10/2016, 10:30
  32. 53. Consolidation
    27/10/2016, 11:15
  33. 52. GPUs and the Heterogeneous programming problem
    Dr Tim Mattson (Intel)
    27/10/2016, 12:15
  34. 54. GPU programming with OpenCL: Ideas and the host program
    Dr Tim Mattson (Intel)
    27/10/2016, 15:30
  35. 55. Consolidation
    27/10/2016, 16:15
  36. 58. Consolidation
    27/10/2016, 17:45
  37. 0. Programming GPUs with OpenCL: Kernel programs
    Dr Tim Mattson (Intel)
    28/10/2016, 08:30
  38. 1. Programming GPUs with OpenCL: Performance issues
    Dr Tim Mattson (Intel)
    28/10/2016, 09:15
  39. 2. Lecture
    28/10/2016, 10:30
  40. 3. Cluster Computing with MPI
    Dr Tim Mattson (Intel)
    28/10/2016, 11:15
  41. 4. Consolidation
    28/10/2016, 12:00
  42. 5. The 10 core constructs every MPI programmer should know
    Dr Tim Mattson (Intel)
    28/10/2016, 14:30
  43. 6. Geometric decomposition and MPI
    Dr Tim Mattson (Intel)
    28/10/2016, 15:45
  44. 7. Information
    Mauro Morandin (PD)
    28/10/2016, 17:00
  45. 8. Consolidation
    28/10/2016, 17:05
  46. 9. Evening lecture: The future of Big Data: Polystore, specialized storage engines, and embedded analytics.
    Dr Tim Mattson (Intel)
    28/10/2016, 18:30
    Theory is nice when trying to understand Big Data systems, but nothing beats experience with real data. Working with the MIMIC II data set (data from an intensive care unit) we've concluded that: 1. Data must match the storage engine if you care about performance 2. Data in flat files is almost equivalent to deleting it. Or, turning these conclusions into slogans, "one size does not fit...
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  47. 37. Students feedback
    29/10/2016, 08:30
  48. 38. Final examination
    29/10/2016, 09:00
  49. 39. Delivery of certificates of attendance
    29/10/2016, 11:30
  50. 40. Shuttle departure (to Forli' railway station)
    29/10/2016, 13:30
  51. 45. Consolidation
  52. 47. Consolidation
  53. 48. Consolidation
  54. 56. Consolidation
  55. 49. Evening lecture: "Low-power computing with System-on-Chips"
    Daniele Cesini (CNAF)
    The embedded and high-performance computing sectors have in the past been very isolated and unaware of each other’s needs and technologies. Similar isolations have occurred between HPC and the mobile/tablets commodity markets. We are now experiencing a very important convergence between markets, both in constraints and needs as well as in technologies. High computational demands, power...
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  56. 41. Floating point computing efficiency
    Vincenzo Innocente (CERN)
  57. 46. GPU programming with OpenCL: Core Ideas and the host program
    Dr Tim Mattson (Intel)
  58. 44. GPUs and the Heterogeneous programming problem
    Dr Tim Mattson (Intel)
  59. 43. Vectorization
    Vincenzo Innocente (CERN)