Topic
SequenceL
About: SequenceL is a research topic. Over the lifetime, 58 publications have been published within this topic receiving 408 citations.
Papers published on a yearly basis
Papers
13 Jun 2011
TL;DR: This paper presents extensions to OpenMP that provide a high-level programming model that can provide accelerated performance comparable to that of hand-coded implementations in CUDA.
Abstract: OpenMP [14] is the dominant programming model for shared-memory parallelism in C, C++ and Fortran due to its easy-touse directive-based style, portability and broad support by compiler vendors. Compute-intensive application regions are increasingly being accelerated using devices such as GPUs and DSPs, and a programming model with similar characteristics is needed here. This paper presents extensions to OpenMP that provide such a programming model. Our results demonstrate that a high-level programming model can provide accelerated performance comparable to that of hand-coded implementations in CUDA.
57 citations
IBM1
TL;DR: It can be shown, for example, that any functional result achievable in a programming language with gotos can be achieved in that same language without gotos if sequence, selection, and iteration control constructs are present.
Abstract: Structured programming introduced a new discipline for accessing the instructions of a program. In suitable programming languages, this discipline can be described in terms of program design without gotos. It can be shown, for example, that any functional result achievable in a programming language with gotos can be achieved in that same language without gotos if sequence, selection, and iteration control constructs are present. The gotos permit random access to the instructions while sequence, selection, and iteration provide much more limited and disciplined access. The authors introduce a new discipline for accessing the data of a program. Any functional result achievable in a programming language with arrays and pointers can be achieved in that same language without arrays and pointers if set, stack, and queue data types are present. The arrays and pointers permit random access to the data while sets, stacks, and queues provide much more limited and disciplined access.
47 citations
TL;DR: It is shown how loop algorithms can be encompassed in an iterator and then activated for any data type for which a generator can be defined, and that selectors can be employed in the definition of a truly generic sorting routine.
Abstract: It is shown how loop algorithms can be encompassed in an iterator and then activated for any data type for which a generator can be defined. It takes the iterator-generator idea a step further than previous work in that it permits variations of the iterators to be defined dynamically through the use of selectors and actors, without loss of efficiency or clarity. It is further shown that selectors can be employed in the definition of a truly generic sorting routine. Guidelines for the decomposition of a system into generic data types, abstract data types, iterators, generators, and the programs that exercise them are given, and several complete programs show the implementation of the techniques in Ada. >
22 citations
TL;DR: This paper serves as a comprehensive introduction to SequenceL, which includes new results and language features.
22 citations
Book•
8 Dec 2010
TL;DR: This book dives deep into the latest technologies available to programmers for creating professional parallel applications using C#, .NET 4, and Visual Studio 2010, and teaches other parallel programming techniques, such as SIMD and vectorization.
Abstract: Expert guidance for those programming todays dual-core processors PCsAs PC processors explode from one or two to now eight processors, there is an urgent need for programmers to master concurrent programming. This book dives deep into the latest technologies available to programmers for creating professional parallel applications using C#, .NET 4, and Visual Studio 2010. The book covers task-based programming, coordination data structures, PLINQ, thread pools, asynchronous programming model, and more. It also teaches other parallel programming techniques, such as SIMD and vectorization.Teaches programmers professional-level, task-based, parallel programming with C#, .NET 4, and Visual Studio 2010Covers concurrent collections, coordinated data structures, PLINQ, thread pools, asynchronous programming model, Visual Studio 2010 debugging, and parallel testing and tuningExplores vectorization, SIMD instructions, and additional parallel librariesMaster the tools and technology you need to develop thread-safe concurrent applications for multi-core systems, with Professional Parallel Programming with C#.
18 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2018 | 1 |
| 2017 | 1 |
| 2016 | 1 |
| 2015 | 3 |
| 2014 | 4 |
| 2013 | 1 |