Tools for High Performance Computing
Michael Resch,Rainer Keller,Valentin Himmler,Bettina Krammer,Alexander Schulz +4 more
- 01 Jan 2008
94
TL;DR: This workshop will give the users an overview of the existing tools in the area of integrated development environments for clusters, various parallel debuggers, and new-style performance analysis tools, as well as an update on the state of the art of long-term research tools, which have advanced to an industrial level.
read more
About: The article was published on 01 Jan 2008. The article focuses on the topics: End-user computing & Supercomputer.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Artificial intelligence in E-Commerce: a bibliometric study and literature review
TL;DR: This paper synthesises research on artificial intelligence (AI) in e-commerce and proposes guidelines on how information systems (IS) research could contribute to this research stream and places China-based institutions as leaders in this researcher area.
159
Scrambled Linear Pseudorandom Number Generators
David Blackman,Sebastiano Vigna +1 more
TL;DR: In this article, the authors introduce two new F2-linear transformations that have been handcrafted to have good statistical properties and at the same time to be programmable very efficiently on superscalar processors, or even directly in hardware.
61
Using the Greenup, Powerup, and Speedup metrics to evaluate software energy efficiency
Sarah Abdulsalam,Ziliang Zong,Qijun Gu,Meikang Qiu +3 more
- 14 Dec 2015
TL;DR: The Greenup, Powerup, and Speedup metrics (GPS-UP) are proposed to categorize software implementation and optimization efficiency and compare them to existing metrics such as Energy Delay Product (EDP).
47
Survey and Analysis of Kernel and Userspace Tracers on Linux: Design, Implementation, and Overhead
Mohamad Gebai,Michel Dagenais +1 more
TL;DR: A hands-on comparison of modern tracers on Linux systems, both in user space and kernel space is presented and microbenchmarks that not only quantify the overhead of different tracers, but also sample fine-grained metrics that unveil insights into the tracers’ internals and show the cause of each tracer’s overhead.
Grizzly: Efficient Stream Processing Through Adaptive Query Compilation
Philipp M. Grulich,Breß Sebastian,Steffen Zeuch,Jonas Traub,Janis von Bleichert,Zongxiong Chen,Tilmann Rabl,Volker Markl +7 more
- 11 Jun 2020
TL;DR: This paper presents Grizzly, a novel adaptive query compilation-based SPE, to enable highly efficient query execution and extends query compilation and task-based parallelization for the unique requirements of stream processing and applies adaptive compilation to enable runtime re-optimizations.
43