Login

Ninth INFN International School on: "Architectures, tools and methodologies for developing efficient large scale scientific computing applications" ESC17 - Bertinoro (Forlì-Cesena) Italy 22-28 October 2017

22–28 Oct 2017
Bertinoro
Europe/Rome timezone

Contribution List

58 out of 58 displayed
Export to PDF
  1. 9. Welcome and introduction
    Mauro Morandin (INFN - Padova)
    23/10/2017, 09:00
  2. 10. Computer Architecture evolution and the performance challenge
    Vincenzo Innocente (CERN)
    23/10/2017, 09:30
  3. 11. Computer Architecture evolution and the performance challenge
    Vincenzo Innocente (CERN)
    23/10/2017, 11:00
  4. 12. Hands-on environment checkout
    Dr Francesco Giacomini (CNAF)
    23/10/2017, 11:45
  5. 14. Efficient C++ programming and memory management
    Dr Francesco Giacomini (CNAF)
    23/10/2017, 14:00
  6. 15. Efficient C++ programming and memory management
    Dr Francesco Giacomini (CNAF)
    23/10/2017, 14:45
  7. 16. Efficient C++ programming and memory management
    Dr Francesco Giacomini (CNAF)
    23/10/2017, 16:00
  8. 17. Consolidation
    23/10/2017, 16:45
  9. 18. Students lightning presentations
    23/10/2017, 17:15
  10. 0. Efficient C++ programming and memory management
    Dr Francesco Giacomini (CNAF)
    24/10/2017, 08:30
  11. 1. Efficient C++ programming and memory management
    Dr Francesco Giacomini (CNAF)
    24/10/2017, 09:15
  12. 2. Efficient C++ programming and memory management
    Francesco Giacomini (CNAF)
    24/10/2017, 10:30
  13. 3. Efficient C++ programming and memory management
    Francesco Giacomini (CNAF)
    24/10/2017, 11:15
  14. 4. Consolidation
    24/10/2017, 12:00
  15. 5. Introduction to parallel computing (basic concepts)
    Dr Tim Mattson (Intel)
    24/10/2017, 15:00
  16. 6. Introduction to parallel computing with OpenMP
    Dr Tim Mattson (Intel)
    24/10/2017, 15:45
  17. 7. Parallel Performance concepts using OpenMP
    Dr Tim Mattson (Intel)
    24/10/2017, 17:00
  18. 8. Students lightning presentations
    24/10/2017, 17:45
  19. 23. Efficient C++ programming and memory management
    Francesco Giacomini (CNAF)
    25/10/2017, 08:30
  20. 24. Efficient C++ programming and memory management
    Francesco Giacomini (CNAF)
    25/10/2017, 09:15
  21. 25. A "Hands-on" introduction to OpenMP
    Dr Tim Mattson (Intel)
    25/10/2017, 10:30
  22. 26. A "Hands-on" introduction to OpenMP
    Dr Tim Mattson (Intel)
    25/10/2017, 11:15
  23. 27. Consolidation
    25/10/2017, 12:00
  24. 28. Working with OpenMP: Performance Optimization
    Dr Tim Mattson (Intel)
    25/10/2017, 15:00
  25. 29. Working with OpenMP: Debugging Applications
    Dr Tim Mattson (Intel)
    25/10/2017, 16:45
  26. 30. Consolidation
    25/10/2017, 17:30
  27. 32. Efficient floating-point computation and vectorization
    Vincenzo Innocente (CERN)
    26/10/2017, 08:30
  28. 33. Efficient floating-point computation and vectorization
    Vincenzo Innocente (CERN)
    26/10/2017, 09:15
  29. 34. Efficient floating-point computation and vectorization
    Vincenzo Innocente (CERN)
    26/10/2017, 10:30
  30. 35. Consolidation
    26/10/2017, 11:15
  31. 36. GPUs and the Heterogeneous programming problem
    Dr Tim Mattson (Intel)
    26/10/2017, 12:15
  32. 37. GPU programming with OpenCL: Ideas and the host program
    Dr Tim Mattson (Intel)
    26/10/2017, 14:30
  33. 38. Consolidation
    26/10/2017, 15:15
  34. 39. Consolidation
    26/10/2017, 16:45
  35. 57. From HPC to Deep Learning, a short journey on modern techniques
    Piero Altoè (NVIDIA)
    26/10/2017, 18:00
    Software design of legacy high-performance computing (HPC) applications is heavily influenced by the frequent changes on the architectures. The classic CPU-based approach with communication libraries is not sufficient to scale beyond the limit of Amdahl law and Dennard scaling. Silicon manufacturers design alternative architectures and programming models to overcome this limitation, leading to...
    Go to contribution page
  36. 40. Programming GPUs with OpenCL: Kernel programs
    Dr Tim Mattson (Intel)
    27/10/2017, 08:30
  37. 41. Using GPUs with other programming models
    Dr Tim Mattson (Intel)
    27/10/2017, 09:15
  38. 42. GPGPU epilog
    27/10/2017, 10:30
  39. 43. Cluster Computing with MPI
    Dr Tim Mattson (Intel)
    27/10/2017, 11:15
  40. 44. Consolidation
    27/10/2017, 12:00
  41. 45. The 10 core constructs every MPI programmer should know
    Dr Tim Mattson (Intel)
    27/10/2017, 14:30
  42. 46. Geometric decomposition and MPI
    Dr Tim Mattson (Intel)
    27/10/2017, 15:45
  43. 47. Information
    Mauro Morandin (PD)
    27/10/2017, 17:00
  44. 48. Consolidation
    27/10/2017, 17:05
  45. 49. Surviving the Red Queen’s Race: A guide for the perplexed programmer
    Dr Tim Mattson (Intel)
    27/10/2017, 18:00
    The Red Queen’s race is an important hypothesis in evolutionary biology raised to explain the impact of competition on the rate of evolution. I submit that it is an excellent analogy for the hardware chaos we are now facing. The question is, what can programmers do to survive as the hardware literally changes underneath them? In this talk we will look at trends in hardware and explore...
    Go to contribution page
  46. 19. Students feedback
    28/10/2017, 08:30
  47. 20. Final examination
    28/10/2017, 09:00
  48. 21. Delivery of certificates of attendance
    28/10/2017, 11:30
  49. 22. Shuttle departure (to Forli' railway station)
    28/10/2017, 13:30
  50. 51. Consolidation
  51. 53. Consolidation
  52. 56. Consolidation
  53. 31. Evening Lecture "Go: a different tack at building concurrent programs that grow with grace"
    Dr Sebastien Binet (LPC/IN2P3)
    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.
    Go to contribution page
  54. 55. Floating point computing efficiency
    Vincenzo Innocente (CERN)
  55. 50. GPU programming with OpenCL: Core Ideas and the host program
    Dr Tim Mattson (Intel)
  56. 52. GPUs and the Heterogeneous programming problem
    Dr Tim Mattson (Intel)
  57. 54. Vectorization
    Vincenzo Innocente (CERN)
  58. 13. Welcome by the Director of the INFN Padova site
    Mauro Mezzetto (PD)