29 research outputs found
Evaluation of DVFS techniques on modern HPC processors and accelerators for energy-aware applications
Energy efficiency is becoming increasingly important for computing systems,
in particular for large scale HPC facilities. In this work we evaluate, from an
user perspective, the use of Dynamic Voltage and Frequency Scaling (DVFS)
techniques, assisted by the power and energy monitoring capabilities of modern
processors in order to tune applications for energy efficiency. We run selected
kernels and a full HPC application on two high-end processors widely used in
the HPC context, namely an NVIDIA K80 GPU and an Intel Haswell CPU. We evaluate
the available trade-offs between energy-to-solution and time-to-solution,
attempting a function-by-function frequency tuning. We finally estimate the
benefits obtainable running the full code on a HPC multi-GPU node, with respect
to default clock frequency governors. We instrument our code to accurately
monitor power consumption and execution time without the need of any additional
hardware, and we enable it to change CPUs and GPUs clock frequencies while
running. We analyze our results on the different architectures using a simple
energy-performance model, and derive a number of energy saving strategies which
can be easily adopted on recent high-end HPC systems for generic applications
Automatic Loop Kernel Analysis and Performance Modeling With Kerncraft
Analytic performance models are essential for understanding the performance
characteristics of loop kernels, which consume a major part of CPU cycles in
computational science. Starting from a validated performance model one can
infer the relevant hardware bottlenecks and promising optimization
opportunities. Unfortunately, analytic performance modeling is often tedious
even for experienced developers since it requires in-depth knowledge about the
hardware and how it interacts with the software. We present the "Kerncraft"
tool, which eases the construction of analytic performance models for streaming
kernels and stencil loop nests. Starting from the loop source code, the problem
size, and a description of the underlying hardware, Kerncraft can ideally
predict the single-core performance and scaling behavior of loops on multicore
processors using the Roofline or the Execution-Cache-Memory (ECM) model. We
describe the operating principles of Kerncraft with its capabilities and
limitations, and we show how it may be used to quickly gain insights by
accelerated analytic modeling.Comment: 11 pages, 4 figures, 8 listing
A Survey of Green Networking Research
Reduction of unnecessary energy consumption is becoming a major concern in
wired networking, because of the potential economical benefits and of its
expected environmental impact. These issues, usually referred to as "green
networking", relate to embedding energy-awareness in the design, in the devices
and in the protocols of networks. In this work, we first formulate a more
precise definition of the "green" attribute. We furthermore identify a few
paradigms that are the key enablers of energy-aware networking research. We
then overview the current state of the art and provide a taxonomy of the
relevant work, with a special focus on wired networking. At a high level, we
identify four branches of green networking research that stem from different
observations on the root causes of energy waste, namely (i) Adaptive Link Rate,
(ii) Interface proxying, (iii) Energy-aware infrastructures and (iv)
Energy-aware applications. In this work, we do not only explore specific
proposals pertaining to each of the above branches, but also offer a
perspective for research.Comment: Index Terms: Green Networking; Wired Networks; Adaptive Link Rate;
Interface Proxying; Energy-aware Infrastructures; Energy-aware Applications.
18 pages, 6 figures, 2 table
3E: Energy-Efficient Elastic Scheduling for Independent Tasks in Heterogeneous Computing Systems
Reducing energy consumption is a major design constraint for modern heterogeneous computing systems to minimize electricity cost, improve system reliability and protect environment. Conventional energy-efficient scheduling strategies developed on these systems do not sufficiently exploit the system elasticity and adaptability for maximum energy savings, and do not simultaneously take account of user expected finish time. In this paper, we develop a novel scheduling strategy named energy-efficient elastic (3E) scheduling for aperiodic, independent and non-real-time tasks with user expected finish times on DVFS-enabled heterogeneous computing systems. The 3E strategy adjusts processors’ supply voltages and frequencies according to the system workload, and makes trade-offs between energy consumption and user expected finish times. Compared with other energy-efficient strategies, 3E significantly improves the scheduling quality and effectively enhances the system elasticity
A Survey of Research on Power Management Techniques for High Performance Systems
This paper surveys the research on power management techniques for high performance systems. These include both commercial high performance clusters and scientific high performance computing (HPC) systems. Power consumption has rapidly risen to an intolerable scale. This results in both high operating costs and high failure rates so it is
now a major cause for concern. It is imposed new challenges to the development of high performance systems. In this paper, we first review the basic mechanisms that underlie power management techniques. Then we survey two fundamental techniques for power
management: metrics and profiling. After that, we review the research for the two major types of high performance systems: commercial clusters and supercomputers. Based on this, we discuss the new opportunities and problems presented by the recent adoption of
virtualization techniques, and again we present the most recent research on this. Finally, we summarise and discuss future research directions
Research challenges on energy-efficient networking design
The networking research community has started looking into key questions on energy efficiency of communication networks. The European Commission activated under the FP7 the TREND Network of Excellence with the goal of establishing the integration of the EU research community in green networking with a long perspective to consolidate the European leadership in the field. TREND integrates the activities of major European players in networking, including manufacturers, operators, research centers, to quantitatively assess the energy demand of current and future telecom infrastructures, and to design energy-efficient, scalable and sustainable future networks. This paper describes the main results of the TREND research community and concludes with a roadmap describing the next steps for standardization, regulation agencies and research in both academia and industry.The research leading to these results has received funding from the EU 7th Framework Programme (FP7/2007–2013) under Grant Agreement No. 257740 (NoE TREND)
A 'cool' load balancer for parallel applications
Meeting power requirements of huge exascale machines of the future would be one major challenge. Our focus in this paper is to minimize cooling power and we propose a tech-nique, that uses a combination of DVFS and temperature aware load balancing to constrain core temperatures as well as save cooling energy. Our scheme is specifically designed to suit parallel applications which are typically tightly coupled. The temperature control comes at the cost of execution time and we try to minimize the timing penalty. We experiment with three applications (with different power utilization profiles), run on a 128-core (32-node) cluster with a dedicated air conditioning unit. We calibrate the efficacy of our scheme based on three metrics: ability to control aver-age core temperatures thereby avoiding hot spot occurence, timing penalty minimization, and cooling energy savings. Our results show cooling energy savings of up to 57 % with timing penalty mostly in the range of 2 to 20%. 1
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