BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CERN//INDICO//EN
BEGIN:VEVENT
SUMMARY:Introduction to CUDA and Parallel Programming
DTSTART;VALUE=DATE-TIME:20181202T070000Z
DTEND;VALUE=DATE-TIME:20181202T083000Z
DTSTAMP;VALUE=DATE-TIME:20260814T181540Z
UID:indico-contribution-186-861@events.chpc.ac.za
DESCRIPTION:Speakers: Rob Farber (TechEnablement)\nDescription:\nThe goal 
 of this workshop is to introduce students to CUDA and provide them with an
  understanding of parallel programming. CUDA is more than a few new keywor
 ds. One must understand SIMD and the pitfalls of serialization. \n\nStuden
 ts will leave with basic CUDA skills and some OpenACC knowledge plus usefu
 l machine learning and big data tools as well. My “from Hello World to e
 xascale machine learning in one slide” will also be covered as data para
 llel training fits on GPUs nicely.\n\nTarget Audience:\nAnyone with C/C++ 
 programming skills in the Unix environment who wishes to learn about paral
 lel programming and  CUDA. The material will be 60% beginner\, 30% interme
 diate\, and 10% advanced. \n\nPrerequisites:\nC/C++ along with an ability 
 to edit and compile programs in a Unix environment\n\nSpecial requirements
 :\nUsers will have access to a CHPC system with GPUs. \n\nAttendees should
  bring their own laptops. The ability to view pdf or PowerPoint files is r
 equired.\n\nOutline of full syllabus:\n08:00	Registration\n09:00	Introduct
 ion and morning talk (30 minutes)\n        Login details and extracting th
 e workshop material (15 minutes)\n        Section 01: Parallel intro and a
  first CUDA program)\n        Section 02: Profiling on a GPU\n\n\n10:30	Mo
 rning Refreshment Break\n11:00	Section 03: More CUDA and the Thrust Interf
 ace\n        Section 04: “From Hello World to TF/s machine learning”\n
 12:30	Lunch\n13:30	Afternoon talk \n        Section 05: Controlling parall
 el resources\n        Section 06: C++ objects and transparent host/GPU dat
 a movement \n15:00	Afternoon Refreshment Break\n15:30	Section 07: Task lev
 el parallelism on a GPU\n        Section 08: Managing big data\, CUDA as a
  scripting language via dynamic load/link\n17:00	End of Day\n\n\nAdditiona
 l Comments:\nStudents can work at their own pace. \nIntroductory students 
 will learn the basics of CUDA and the profiler as well as how to think in 
 parallel and understand the impact of parallel hardware on performance.\nI
 ntermediate/advanced students will hone their thinking about parallel prog
 ramming and the limitations and advantages of GPU hardware. Extra credit e
 xercises will challenge them.\nAll students will learn how to use machine 
 learning and the ability to explore this hot field and leave with a tool t
 hat allows them to train and predict using their own data sets and neural 
 network architectures. Further\, they learn how to work with and collabora
 te using big data.\n\nhttps://events.chpc.ac.za/event/33/contributions/861
 /
LOCATION: Meeting Room 10
URL:https://events.chpc.ac.za/event/33/contributions/861/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Introduction to CUDA and Parallel Programming
DTSTART;VALUE=DATE-TIME:20181202T133000Z
DTEND;VALUE=DATE-TIME:20181202T150000Z
DTSTAMP;VALUE=DATE-TIME:20260814T181540Z
UID:indico-contribution-186-865@events.chpc.ac.za
DESCRIPTION:Speakers: Rob Farber (TechEnablement)\nDescription:\nThe goal 
 of this workshop is to introduce students to CUDA and provide them with an
  understanding of parallel programming. CUDA is more than a few new keywor
 ds. One must understand SIMD and the pitfalls of serialization. \n\nStuden
 ts will leave with basic CUDA skills and some OpenACC knowledge plus usefu
 l machine learning and big data tools as well. My “from Hello World to e
 xascale machine learning in one slide” will also be covered as data para
 llel training fits on GPUs nicely.\n\nTarget Audience:\nAnyone with C/C++ 
 programming skills in the Unix environment who wishes to learn about paral
 lel programming and  CUDA. The material will be 60% beginner\, 30% interme
 diate\, and 10% advanced. \n\nPrerequisites:\nC/C++ along with an ability 
 to edit and compile programs in a Unix environment\n\nSpecial requirements
 :\nUsers will have access to a CHPC system with GPUs. \n\nAttendees should
  bring their own laptops. The ability to view pdf or PowerPoint files is r
 equired.\n\nOutline of full syllabus:\n08:00	Registration\n09:00	Introduct
 ion and morning talk (30 minutes)\n        Login details and extracting th
 e workshop material (15 minutes)\n        Section 01: Parallel intro and a
  first CUDA program)\n        Section 02: Profiling on a GPU\n\n\n10:30	Mo
 rning Refreshment Break\n11:00	Section 03: More CUDA and the Thrust Interf
 ace\n        Section 04: “From Hello World to TF/s machine learning”\n
 12:30	Lunch\n13:30	Afternoon talk \n        Section 05: Controlling parall
 el resources\n        Section 06: C++ objects and transparent host/GPU dat
 a movement \n15:00	Afternoon Refreshment Break\n15:30	Section 07: Task lev
 el parallelism on a GPU\n        Section 08: Managing big data\, CUDA as a
  scripting language via dynamic load/link\n17:00	End of Day\n\n\nAdditiona
 l Comments:\nStudents can work at their own pace. \nIntroductory students 
 will learn the basics of CUDA and the profiler as well as how to think in 
 parallel and understand the impact of parallel hardware on performance.\nI
 ntermediate/advanced students will hone their thinking about parallel prog
 ramming and the limitations and advantages of GPU hardware. Extra credit e
 xercises will challenge them.\nAll students will learn how to use machine 
 learning and the ability to explore this hot field and leave with a tool t
 hat allows them to train and predict using their own data sets and neural 
 network architectures. Further\, they learn how to work with and collabora
 te using big data.\n\nhttps://events.chpc.ac.za/event/33/contributions/865
 /
LOCATION: Meeting Room 10
URL:https://events.chpc.ac.za/event/33/contributions/865/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Introduction to CUDA and Parallel Programming
DTSTART;VALUE=DATE-TIME:20181202T090000Z
DTEND;VALUE=DATE-TIME:20181202T103000Z
DTSTAMP;VALUE=DATE-TIME:20260814T181540Z
UID:indico-contribution-186-863@events.chpc.ac.za
DESCRIPTION:Speakers: Rob Farber (TechEnablement)\nDescription:\nThe goal 
 of this workshop is to introduce students to CUDA and provide them with an
  understanding of parallel programming. CUDA is more than a few new keywor
 ds. One must understand SIMD and the pitfalls of serialization. \n\nStuden
 ts will leave with basic CUDA skills and some OpenACC knowledge plus usefu
 l machine learning and big data tools as well. My “from Hello World to e
 xascale machine learning in one slide” will also be covered as data para
 llel training fits on GPUs nicely.\n\nTarget Audience:\nAnyone with C/C++ 
 programming skills in the Unix environment who wishes to learn about paral
 lel programming and  CUDA. The material will be 60% beginner\, 30% interme
 diate\, and 10% advanced. \n\nPrerequisites:\nC/C++ along with an ability 
 to edit and compile programs in a Unix environment\n\nSpecial requirements
 :\nUsers will have access to a CHPC system with GPUs. \n\nAttendees should
  bring their own laptops. The ability to view pdf or PowerPoint files is r
 equired.\n\nOutline of full syllabus:\n08:00	Registration\n09:00	Introduct
 ion and morning talk (30 minutes)\n        Login details and extracting th
 e workshop material (15 minutes)\n        Section 01: Parallel intro and a
  first CUDA program)\n        Section 02: Profiling on a GPU\n\n\n10:30	Mo
 rning Refreshment Break\n11:00	Section 03: More CUDA and the Thrust Interf
 ace\n        Section 04: “From Hello World to TF/s machine learning”\n
 12:30	Lunch\n13:30	Afternoon talk \n        Section 05: Controlling parall
 el resources\n        Section 06: C++ objects and transparent host/GPU dat
 a movement \n15:00	Afternoon Refreshment Break\n15:30	Section 07: Task lev
 el parallelism on a GPU\n        Section 08: Managing big data\, CUDA as a
  scripting language via dynamic load/link\n17:00	End of Day\n\n\nAdditiona
 l Comments:\nStudents can work at their own pace. \nIntroductory students 
 will learn the basics of CUDA and the profiler as well as how to think in 
 parallel and understand the impact of parallel hardware on performance.\nI
 ntermediate/advanced students will hone their thinking about parallel prog
 ramming and the limitations and advantages of GPU hardware. Extra credit e
 xercises will challenge them.\nAll students will learn how to use machine 
 learning and the ability to explore this hot field and leave with a tool t
 hat allows them to train and predict using their own data sets and neural 
 network architectures. Further\, they learn how to work with and collabora
 te using big data.\n\nhttps://events.chpc.ac.za/event/33/contributions/863
 /
LOCATION: Meeting Room 10
URL:https://events.chpc.ac.za/event/33/contributions/863/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Introduction to CUDA and Parallel Programming
DTSTART;VALUE=DATE-TIME:20181202T113000Z
DTEND;VALUE=DATE-TIME:20181202T130000Z
DTSTAMP;VALUE=DATE-TIME:20260814T181540Z
UID:indico-contribution-186-864@events.chpc.ac.za
DESCRIPTION:Speakers: Rob Farber (TechEnablement)\nDescription:\nThe goal 
 of this workshop is to introduce students to CUDA and provide them with an
  understanding of parallel programming. CUDA is more than a few new keywor
 ds. One must understand SIMD and the pitfalls of serialization. \n\nStuden
 ts will leave with basic CUDA skills and some OpenACC knowledge plus usefu
 l machine learning and big data tools as well. My “from Hello World to e
 xascale machine learning in one slide” will also be covered as data para
 llel training fits on GPUs nicely.\n\nTarget Audience:\nAnyone with C/C++ 
 programming skills in the Unix environment who wishes to learn about paral
 lel programming and  CUDA. The material will be 60% beginner\, 30% interme
 diate\, and 10% advanced. \n\nPrerequisites:\nC/C++ along with an ability 
 to edit and compile programs in a Unix environment\n\nSpecial requirements
 :\nUsers will have access to a CHPC system with GPUs. \n\nAttendees should
  bring their own laptops. The ability to view pdf or PowerPoint files is r
 equired.\n\nOutline of full syllabus:\n08:00	Registration\n09:00	Introduct
 ion and morning talk (30 minutes)\n        Login details and extracting th
 e workshop material (15 minutes)\n        Section 01: Parallel intro and a
  first CUDA program)\n        Section 02: Profiling on a GPU\n\n\n10:30	Mo
 rning Refreshment Break\n11:00	Section 03: More CUDA and the Thrust Interf
 ace\n        Section 04: “From Hello World to TF/s machine learning”\n
 12:30	Lunch\n13:30	Afternoon talk \n        Section 05: Controlling parall
 el resources\n        Section 06: C++ objects and transparent host/GPU dat
 a movement \n15:00	Afternoon Refreshment Break\n15:30	Section 07: Task lev
 el parallelism on a GPU\n        Section 08: Managing big data\, CUDA as a
  scripting language via dynamic load/link\n17:00	End of Day\n\n\nAdditiona
 l Comments:\nStudents can work at their own pace. \nIntroductory students 
 will learn the basics of CUDA and the profiler as well as how to think in 
 parallel and understand the impact of parallel hardware on performance.\nI
 ntermediate/advanced students will hone their thinking about parallel prog
 ramming and the limitations and advantages of GPU hardware. Extra credit e
 xercises will challenge them.\nAll students will learn how to use machine 
 learning and the ability to explore this hot field and leave with a tool t
 hat allows them to train and predict using their own data sets and neural 
 network architectures. Further\, they learn how to work with and collabora
 te using big data.\n\nhttps://events.chpc.ac.za/event/33/contributions/864
 /
LOCATION: Meeting Room 10
URL:https://events.chpc.ac.za/event/33/contributions/864/
END:VEVENT
END:VCALENDAR