Swedish web site
Multicore computingDF21500, 2011VTFull
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Course plan
Lectures
Ca. 32h, given in block format in 2 intensive weeks in February and early March 2011.
Recommended for
Graduate (CUGS, CIS, ISY, ...) students interested in the areas of parallel computer architecture, parallel programming, software engineering, optimization, compiler construction, or algorithms and complexity.
The course was last given
in VT2009.
Goals
The course emphasizes fundamental aspects of shared-memory parallel programming such as shared memory parallel architecture concepts, programming models, performance models, parallel algorithmic paradigms, parallelization techniques and strategies, scheduling algorithms, optimization, composition of parallel programs, and concepts of modern parallel programming languages and systems. Practical exercises help to apply the theoretical concepts of the course to solve concrete problems in a real-world multicore system.
Prerequisites
Data structures and algorithms are absolutely required; some knowledge in
complexity theory and compiler construction is useful. Some basic knowledge of
computer architecture is assumed. A basic course in concurrent programming
(e.g. TDDB68) and parallel programming (e.g. TDDC78 or TANA77) are recommended.
Programming in C and some familiarity with Linux (or similar OS) is necessary
for the practical exercises.
Contents
(some advanced topics may be added or changed depending on availability of
guest lecturers)
I. Architecture
* Multicore architecture issues (incl SMT, SMP, CC-NUMA, NCC-NUMA)
* Short repetition: Cache locality and memory hierarchy
* Shared memory emulation and consistency issues
* Heterogeneous multicores
* GPU computing
II. Languages and environments
* pthreads
* Cilk
* UPC
* OpenMP 3.0
* New HPC languages: X10, Chapel, Fortress
* Stream processing and GPU languages: Cg, Brook, Cuda, OpenCL
* Offload C++
III. Parallelization techniques
* Design patterns for concurrency / synchronization
* Dependence analysis
* Automatic parallelization
* Runtime parallelization and speculative parallelization
* Lock-free synchronization
* Transactional programming
* Task scheduling and clustering
IV. Optimizations
* Feedback directed optimization
* Task mapping and on-chip pipelining
* Skeleton based parallel programming
* Optimized composition of parallel programs from parallel components
* Scheduling malleable task graphs
Organization
Lectures (ca. 32h), programming exercises, optional theoretical exercises for
self-assessment, programming lab assignment, student presentations.
The lecture series of the course will be held in block format with two
intensive weeks in Linköping.
Literature
To be announced on the course homepage.
Lecturers
Christoph Kessler, Linköpings universitet
Welf Löwe, Univ. Växjö, and further guest lecturers
Examiner
Christoph Kessler, Linköpings universitet
Examination
TEN1: Written exam 4.5hp.
UPG1: Programming exercise (lab report) 1.5hp.
UPG2: Paper presentation, opposition, and written summary (1-2 pages) of the
presented paper, 1.5hp.
Credit
7.5hp if all examination moments are fulfilled.
Partial credits can be given, too.
Organized by
CUGS
Comments
There is a partial overlap in contents with FDA125 Advanced Parallel
Programming, which corresponds to 1p = 1.5hp in the written exam.
In contrast to FDA125, we focus in this course on shared memory systems and add
more material on software engineering techniques for parallel systems, such as
design patterns for synchronization and optimized composition of parallel
components. We also give more emphasis to parallelization techniques that are
especially useful for multicore systems, such as speculative parallelization,
transactional programming and lock-free synchronization. Scheduling for shared
memory systems will be considered in more detail, in particular scheduling
algorithms for malleable task graphs.
Page responsible: Director of Graduate Studies
