The document discusses integrating parallel computing concepts into computer science curricula. It argues that while high-performance computing applied to specific domains is a specialization, foundational parallel techniques like distributed computing, multi-threading, and GPU programming should be part of the general curriculum. It also asserts that parallelism needs to be incorporated throughout the entire curriculum since modern computer architectures are inherently parallel.

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Kevin Goldsmith | Senior Software Development Manager
Parallelism, the Cloud, and the Tools of the Future for the next
generation of practitioners

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HPC and the CS Curriculum
§ HPC as applied to specific domains is a specialization or concentration
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3. © 2011 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.
HPC and the CS Curriculum
§ HPC as applied to specific domains is a specialization or concentration
§ The foundational techniques of HPC should be part of the general curriculum
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HPC and the CS Curriculum
§ HPC as applied to specific domains is a specialization or concentration
§ The foundational techniques of HPC should be part of the general curriculum
§ Distributed Computing
§ Multi-threading
§ GPGPU
§ Algorithms
§ Data Structures
§ Design Patterns
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HPC and the CS Curriculum
§ HPC as applied to specific domains is a specialization or concentration
§ The foundational techniques of HPC should be part of the general curriculum
§ Distributed Computing
§ Multi-threading
§ GPGPU
§ Algorithms
§ Data Structures
§ Design Patterns
§ HPC is moving mainstream
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My Current Product
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My Current Product
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ü Data Parallelism
ü SIMD, GPGPU
ü Task Parallelism
ü Reactive Architecture
ü Grand Central Dispatch
ü Distributed Computing
ü AWS-based web services
ü Scale up to 100s of servers

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Understanding Parallelism Means
§ Understanding computer architecture
§ Understanding low-level threading implementations
§ Task-level parallelism
§ Data-level parallelism
§ Race Conditions
§ Lock-Free data structures
§ Strategies for mapping algorithms to parallel architectures efficiently
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Can’t I Use Higher Level Abstractions to Teach Parallelism?
§ Higher-level abstractions provide good starting places for introductory classes
§ How does a student know to choose one abstraction over another?
§ High level abstractions come in and out of favor
§ Students must know when they should abandon the abstraction and go to a
lower level library for a problem
Once students understand parallelism they should feel free to use higher-level
libraries if it suits their projects
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Abstractions for CS Education
§ Introductory CS
§ OpenMP or C++11
§ Algorithms
§ TBB, GCD, OpenCL
§ Computer Architecture
§ pThreads, SSE
§ Server programming
§ Hadoop
§ Software Engineering, Specialized Courses
§ Student’s choice
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Parallelism Must Be Integrated Through the Entire CS Curriculum
§ All Modern Computer Architectures Are Parallel
§ Parallelism can’t be confined to a single class or a section of another class
§ Parallel techniques and algorithms need to be part of every class
§ Students must learn the basics because the hardware and techniques are
continuing to evolve
§ The industry needs students who are proficient in parallel programming
techniques and will expect applicants to demonstrate that skill
Will your students be ready?
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