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Lecture

Parallel Programming I

In course

CS-471: Advanced multiprocessor architecture

Multiprocessors are basic building blocks for all computer systems. This course covers the architecture and organization of modern multiprocessors, prevalent accelerators (e.g., GPU, TPU), and datacenters. It includes a research project on multiprocessors ...

Description

This lecture introduces the fundamentals of parallel programming, covering concepts such as concurrency, parallelism, forms of parallelism (throughput, functional, pipeline, data), task granularity, division of work, asynchrony, creating parallel programs, shared memory programming, automatic parallel program creation, forms of communication (shared memory, message passing), programming models (sequential, shared memory, message passing, data parallel, dataflow), software layering, synchronization, and examples of parallel programming using PThreads and OpenMP.

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Instructor

Babak Falsafi

Babak is a Professor in the School of Computer and Communication Sciences and the founding director of the EcoCloud, an industrial/academic consortium at EPFL investigating scalable data-centric technologies. He has made numerous contributions to computer system design and evaluation including a scalable multiprocessor architecture which was prototyped by Sun Microsystems (now Oracle), snoop filters and memory streaming technologies that are incorporated into IBM BlueGene/P and Q and ARM cores, and computer system performance evaluation methodologies that have been in use by AMD, HP and Google PerKit . He has shown that hardware memory consistency models are neither necessary (in the 90's) nor sufficient (a decade later) to achieve high performance in multiprocessor systems. These results eventually led to fence speculation in modern microprocessors. His latest work on workload-optimized server processors laid the foundation for the first generation of Cavium ARM server CPUs, ThunderX. He is a recipient of an NSF CAREER award, IBM Faculty Partnership Awards, and an Alfred P. Sloan Research Fellowship. He is a fellow of IEEE and ACM.

Official source

Ontological neighbourhood

Computer engineering

High-performance computing: Parallel computing

Related concepts (32)

Parallel programming model

In computing, a parallel programming model is an abstraction of parallel computer architecture, with which it is convenient to express algorithms and their composition in programs. The value of a programming model can be judged on its generality: how well a range of different problems can be expressed for a variety of different architectures, and its performance: how efficiently the compiled programs can execute. The implementation of a parallel programming model can take the form of a library invoked from a sequential language, as an extension to an existing language, or as an entirely new language.

Parallel computing

Parallel computing is a type of computation in which many calculations or processes are carried out simultaneously. Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism. Parallelism has long been employed in high-performance computing, but has gained broader interest due to the physical constraints preventing frequency scaling.

Data parallelism

Data parallelism is parallelization across multiple processors in parallel computing environments. It focuses on distributing the data across different nodes, which operate on the data in parallel. It can be applied on regular data structures like arrays and matrices by working on each element in parallel. It contrasts to task parallelism as another form of parallelism. A data parallel job on an array of n elements can be divided equally among all the processors.

Pthreads

In computing, POSIX Threads, commonly known as pthreads, is an execution model that exists independently from a programming language, as well as a parallel execution model. It allows a program to control multiple different flows of work that overlap in time. Each flow of work is referred to as a thread, and creation and control over these flows is achieved by making calls to the POSIX Threads API. POSIX Threads is an API defined by the Institute of Electrical and Electronics Engineers (IEEE) standard POSIX.

Message Passing Interface

Message Passing Interface (MPI) is a standardized and portable message-passing standard designed to function on parallel computing architectures. The MPI standard defines the syntax and semantics of library routines that are useful to a wide range of users writing portable message-passing programs in C, C++, and Fortran. There are several open-source MPI implementations, which fostered the development of a parallel software industry, and encouraged development of portable and scalable large-scale parallel applications.

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Transitioning to Multithreaded Programming: Key Concepts

Covers the transition from single-threaded to multithreaded programming, focusing on memory models and consistency issues.

Monitors: Synchronization and Cooperation

Explores monitors as a synchronization construct providing mutual exclusion and cooperation among threads, with examples like the one-place buffer.

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