High-performance computing systems: Status and outlook

Acta Numerica ◽  
2012 ◽  
Vol 21 ◽  
pp. 379-474 ◽  
Author(s):  
J. J. Dongarra ◽  
A. J. van der Steen
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
State Of The Art ◽  
Computing Systems ◽  
Future Developments ◽  
Steady Growth ◽  
Current State ◽  
Near Future ◽  
Performance Computing ◽  
Shed Light

This article describes the current state of the art of high-performance computing systems, and attempts to shed light on near-future developments that might prolong the steady growth in speed of such systems, which has been one of their most remarkable characteristics. We review the different ways devised to speed them up, both with regard to components and their architecture. In addition, we discuss the requirements for software that can take advantage of existing and future architectures.

GPU Scaling

2014 ◽  
Vol 9 (4) ◽  
pp. 13-23
Author(s):  
Yaser Jararweh ◽  
Moath Jarrah ◽  
Abdelkader Bousselham
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Gpu Computing ◽  
State Of The Art ◽  
Computing Systems ◽  
Current State ◽  
Viable Solution ◽  
Order Of Magnitude ◽  
Computational Resources ◽  
Performance Computing

Current state-of-the-art GPU-based systems offer unprecedented performance advantages through accelerating the most compute-intensive portions of applications by an order of magnitude. GPU computing presents a viable solution for the ever-increasing complexities in applications and the growing demands for immense computational resources. In this paper the authors investigate different platforms of GPU-based systems, starting from the Personal Supercomputing (PSC) to cloud-based GPU systems. The authors explore and evaluate the GPU-based platforms and the authors present a comparison discussion against the conventional high performance cluster-based computing systems. The authors' evaluation shows potential advantages of using GPU-based systems for high performance computing applications while meeting different scaling granularities.

GPU Scaling

2016 ◽  
pp. 2373-2384
Author(s):  
Yaser Jararweh ◽  
Moath Jarrah ◽  
Abdelkader Bousselham
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Gpu Computing ◽  
State Of The Art ◽  
Computing Systems ◽  
Current State ◽  
Viable Solution ◽  
Order Of Magnitude ◽  
Computational Resources ◽  
Performance Computing

Current state-of-the-art GPU-based systems offer unprecedented performance advantages through accelerating the most compute-intensive portions of applications by an order of magnitude. GPU computing presents a viable solution for the ever-increasing complexities in applications and the growing demands for immense computational resources. In this paper the authors investigate different platforms of GPU-based systems, starting from the Personal Supercomputing (PSC) to cloud-based GPU systems. The authors explore and evaluate the GPU-based platforms and the authors present a comparison discussion against the conventional high performance cluster-based computing systems. The authors' evaluation shows potential advantages of using GPU-based systems for high performance computing applications while meeting different scaling granularities.

A survey of high-performance computing scaling challenges

2016 ◽  
Vol 31 (1) ◽  
pp. 104-113 ◽  
Author(s):  
Al Geist ◽  
Daniel A Reed
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
State Of The Art ◽  
Operational Experience ◽  
Computing Systems ◽  
Software Complexity ◽  
Petascale Computing ◽  
New Challenges ◽  
Commodity Clusters ◽  
Performance Computing

Commodity clusters revolutionized high-performance computing when they first appeared two decades ago. As scale and complexity have grown, new challenges in reliability and systemic resilience, energy efficiency and optimization and software complexity have emerged that suggest the need for re-evaluation of current approaches. This paper reviews the state of the art and reflects on some of the challenges likely to be faced when building trans-petascale computing systems, using insights and perspectives drawn from operational experience and community debates.

scholarly journals Survey of Methodologies, Approaches, and Challenges in Parallel Programming Using High-Performance Computing Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-19 ◽  
Author(s):  
Paweł Czarnul ◽  
Jerzy Proficz ◽  
Krzysztof Drypczewski
Keyword(s):  
High Performance Computing ◽  
Parallel Programming ◽  
High Performance ◽  
Programming Model ◽  
Parallel Execution ◽  
Target System ◽  
Computing Systems ◽  
Programming Abstraction ◽  
Near Future ◽  
Performance Computing

This paper provides a review of contemporary methodologies and APIs for parallel programming, with representative technologies selected in terms of target system type (shared memory, distributed, and hybrid), communication patterns (one-sided and two-sided), and programming abstraction level. We analyze representatives in terms of many aspects including programming model, languages, supported platforms, license, optimization goals, ease of programming, debugging, deployment, portability, level of parallelism, constructs enabling parallelism and synchronization, features introduced in recent versions indicating trends, support for hybridity in parallel execution, and disadvantages. Such detailed analysis has led us to the identification of trends in high-performance computing and of the challenges to be addressed in the near future. It can help to shape future versions of programming standards, select technologies best matching programmers’ needs, and avoid potential difficulties while using high-performance computing systems.

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