1,720,976 research outputs found
Co-scheduling tasks on multi-core heterogeneous systems: An energy-aware perspective
No full textSingle-ISA heterogeneous multi-core processors trade-off power with performance; however, threads that co-
run on shared resources suffer from resource contention, which induces performance degradation and energy
inefficiency. The authors introduce a novel approach to optimise the co-scheduling of multi-threaded applications on
heterogeneous processors. The approach is based on the concept of stakes function, which represents the trade-off
between isolation and sharing of resources. The authors also develop a co-scheduling algorithm that use stakes
functions to optimise resource usage while mitigating resource contention, thus improving performance and energy
efficiency. They validated the approach using applications from the Princeton Application Repository for Shared-
Memory Computers (PARSEC) benchmark suite, obtaining up to 12.88% performance speed-up, 13.65% energy speed-
up and 28.29% energy delay speed-up with respect to the standard Linux heterogeneous multi-processing scheduler
Resource-Aware Application Execution Exploiting the BarbequeRTRM
Full text linkEnergy efficiency and thermal management have become ma- jor concerns in both embedded and HPC systems. The progress of silicon technology and the subsequent growth of the dark silicon phenomena are negatively a ecting the reliability of computing systems. As a result, in the next future we expect run-time variability to increase in terms of both performance and computing resources availability. To address these is- sues, systems and applications must be able to adapt to such scenarios. This work provides a brief overview of the Barbeque Run-Time Resource Manager (BarbequeRTRM) and the application execution model that it exploits, in order to deal with run-time performance and available re- sources variability
Exploiting performance counters for energy efficient co-scheduling of mixed workloads on multi-core platforms
No full textThe MIG Framework: Enabling Transparent Process Migration in Open MPI
Full text linkThis paper introduces the mig framework: an Open MPI extension to transparently support the migration of application processes, over different nodes of a distributed High-Performance Computing (HPC) system. The framework provides mechanism on top of which suitable resource managers can implement policies to react to hardware faults, address performance variability, improve resource utilization, perform a fine-grained load balancing and power thermal management.
Compared to other state-of-the-art approaches, the mig framework does not require changes in the application code. Moreover, it is highly maintainable, since it is mainly a self-contained solution that has required a very few changes in other already existing Open MPI frameworks. Experimental results have shown that the proposed extension does not introduce significant overhead in the application execution, while the penalty due to performing a migration can be properly taken into account by a resource manager
TEST: Assessing NoC policies facing aging and leakage power
No full textThe trend to increase the number of cores integrated on a single die makes Networks-on-Chip (NoCs) a key component from the interconnection viewpoint. Unfortunately, continuous scaling of CMOS technology poses severe concerns regarding failure mechanisms, such as NBTI, that are crucial in achieving a reasonable component lifetime. Furthermore, the leakage power became more and more a critical issues as the technology scales up. Finally, Process Variation (PV) makes harder the scenario, decreasing device lifetime and performance predictability during chip fabrication. Several techniques have been presented in literature facing the NBTI and or the static power consumption. This paper proposes a methodology to analyze such techniques from the feasibility viewpoint. It is explored their effectiveness in contrasting NBTI and saving static power in the NoC as well as the associated overheads and drawbacks. For the two considered policies, it is achieved a NBTI mitigation up to 55% and a power saving up to 51% with performance and area overheads less than 10% and 5%, respectively
Precision-Aware application execution for Energy-optimization in HPC node system
Full text linkPower consumption is a critical consideration in high performance computing
systems and it is becoming the limiting factor to build and operate Petascale
and Exascale systems. When studying the power consumption of existing systems
running HPC workloads, we find that power, energy and performance are closely
related which leads to the possibility to optimize energy consumption without
sacrificing (much or at all) the performance. In this paper, we propose a HPC
system running with a GNU/Linux OS and a Real Time Resource Manager (RTRM) that
is aware and monitors the healthy of the platform. On the system, an
application for disaster management runs. The application can run with
different QoS depending on the situation. We defined two main situations.
Normal execution, when there is no risk of a disaster, even though we still
have to run the system to look ahead in the near future if the situation
changes suddenly. In the second scenario, the possibilities for a disaster are
very high. Then the allocation of more resources for improving the precision
and the human decision has to be taken into account. The paper shows that at
design time, it is possible to describe different optimal points that are going
to be used at runtime by the RTOS with the application. This environment helps
to the system that must run 24/7 in saving energy with the trade-off of losing
precision. The paper shows a model execution which can improve the precision of
results by 65% in average by increasing the number of iterations from 1e3 to
1e4. This also produces one order of magnitude longer execution time which
leads to the need to use a multi-node solution. The optimal trade-off between
precision vs. execution time is computed by the RTOS with the time overhead
less than 10% against a native execution
Simulation of a runoff model running with multi-criteria in a cluster system
No full textThis paper shows simulations aspects of a Scenario-based run-time task mapping application. The application falls into the category of hydrologic prediction based on meteorological forecast. These applications demand computational resources, which depend on the scenario. In our case the study is focused partly on the rainfall-runoff model, the uncertainties that have to be computed with time constraints and with a minimum requirement of quality (i.e. precision).
The main aim of this paper is to detect the simulation aspects and the trade-offs (such as power vs. time) which give a runtime manager running a safety-critical system. It shows two scenarios, the first a multi-core machine where several instances of the model have to compete for resources. And the second one presents the range of High Performance Computing resources needed to compute such model that can vary significantly depending on the scenario
A runtime controller for OpenCL applications on heterogeneous system architectures
No full textHeterogeneous architectures nowadays are becoming very at-tractive in the embedded and mobile markets thanks to the possibility to exploit the best computational resource to op-timize the performance per Watt figure of merit. Unfortu-nately, deciding the right resource to use and its operating frequency is a difficult problem that depends on the actual conditions in which the system is operating. This work aims at proposing a runtime controller, integrated in Linux Oper-ating System (OS), for optimizing the power efficiency of a running application deciding the system configuration. Our experimental results over a set of applications from the Poly-bench suite on the Odroid XU3 board show that our con-troller is able to obtain a power efficiency of more than 90% of the one achievable via offline profiling
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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