| 1. |
- Benkner, S., et al.
(författare)
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Peppher: Performance Portability and Programmability for Heterogeneous Many-Core Architectures
- 2017
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Ingår i: Programming Multicore and Many-Core Computing Systems. - Hoboken, NJ, USA : John Wiley & Sons, Inc.. - 9781119332015 - 9780470936900 ; , s. 241-260
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- © 2017 by John Wiley & Sons, Inc. All rights reserved. PEPPHER takes a pluralistic and parallelization agnostic approach to programmability and performance portability for heterogeneous many-core architectures. The PEPPHER framework is in principle language independent but focuses on supporting C++ code with PEPPHER-specific annotations as pragmas or external annotations. The framework is open and extensible; the PEPPHER methodology details how new architectures are incorporated. The PEPPHER methodology consists of rules for how to extend the framework for new architectures. This mainly concerns adaptivity and autotuning for algorithm libraries, the necessary hooks and extensions for the run-time system and any supporting algorithms and data structures that this relies on. Offloading is a specific technique for programming heterogeneous platforms that can sometimes be applied with high efficiency. Offload as developed by the PEPPHER partner Codeplay is a particular, nonintrusive C++ extension allowing portable C++ code to support diverse heterogeneous multicore architectures in a single code base.
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| 2. |
- Cederman, Daniel, 1981, et al.
(författare)
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Lock-Free Concurrent Data Structures
- 2017
-
Ingår i: Programming multi-core and many-core computing systems. - Hoboken, NJ, USA : John Wiley & Sons, Inc.. - 9781119332015 ; , s. 29-58
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- © 2017 by John Wiley & Sons, Inc. All rights reserved. Concurrent data structures are the data sharing side of parallel programming. An implementation of a data structure is called lock-free, if it allows multiple processes/hreads to access the data structure concurrently and also guarantees that at least one operation among those finishes in a finite number of its own steps regardless of the state of the other operations. This chapter provides a sufficient background and intuition to help the interested reader to navigate in the complex research area of lock-free data structures. It offers the programmer familiarity to the subject that allows using truly concurrent methods. The chapter discusses the fundamental synchronization primitives on which efficient lock-free data structures rely. It discusses the problem of managing dynamically allocated memory in lock-free concurrent data structures and general concurrent environments. The idiosyncratic architectural features of graphics processors that is important to consider when designing efficient lock-free concurrent data structures for this emerging area.
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