Globally scheduled real-time multiprocessor systems with GPUs

Elliott, Glenn A.; Anderson, James H.

doi:10.1007/s11241-011-9140-y

Cited by 64 publications

(48 citation statements)

References 19 publications

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“…Studies on real-time scheduling for GPUs and heterogeneous processors [14][15][16] focus on the scheduling algorithms to use them in real-time applications, while assuming the WCET of the real-time tasks is known. This indicates the importance of the time predictability of GPUs.…”

Section: Related Workmentioning

confidence: 99%

Warp-Based Load/Store Reordering to Improve GPU Time Predictability

Huangfu¹,

Zhang²

2017

Journal of Computing Science and Engineering

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While graphics processing units (GPUs) can be used to improve the performance of real-time embedded applications that require high throughput, it is challenging to estimate the worst-case execution time (WCET) of GPU programs, because modern GPUs are designed for improving the average-case performance rather than time predictability. In this paper, a reordering framework is proposed to regulate the access to the GPU data cache, which helps to improve the accuracy of the estimation of GPU L1 data cache miss rate with low performance overhead. Also, with the improved cache miss rate estimation, tighter WCET estimations can be achieved for GPU programs.

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Section: Related Workmentioning

confidence: 99%

Warp-Based Load/Store Reordering to Improve GPU Time Predictability

Huangfu¹,

Zhang²

2017

Journal of Computing Science and Engineering

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“…While GPUs have been traditionally used for graphics and throughputoriented applications, in recent years the idea of using GPUs to perform real-time processing has been proposed [EA11], [EA12]. In [EA11], the authors explore possible applications for GPUs in real-time systems, summarizing the challenges and limitations, and discussing possible solutions to address them.…”

Section: Real-time Computing On Gpusmentioning

confidence: 99%

“…In [EA11], the authors explore possible applications for GPUs in real-time systems, summarizing the challenges and limitations, and discussing possible solutions to address them. In [EA12], the same authors present two analysis methods that permit the integration of GPUs in soft real-time multiprocessor systems. They follow up their work in [EWA13], where they propose and analyze GPUSync, a highly configurable real-time GPU management framework.…”

Section: Real-time Computing On Gpusmentioning

confidence: 99%

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Hardware/Software Codesign of Embedded Systems with Reconfigurable and Heterogeneous Platforms

Lifa¹

2015

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M odern applications running on today's embedded systems have very high requirements. Most often, these requirements have many dimensions: the applications need high performance as well as flexibility, energyefficiency as well as real-time properties, fault tolerance as well as low cost. In order to meet these demands, the industry is adopting architectures that are more and more heterogeneous and that have reconfiguration capabilities. Unfortunately, this adds to the complexity of designing streamlined applications that can leverage the advantages of such architectures.In this context, it is very important to have appropriate tools and design methodologies for the optimization of such systems. This thesis addresses the topic of hardware/software codesign and optimization of adaptive real-time systems implemented on reconfigurable and heterogeneous platforms. We focus on performance enhancement for dynamically reconfigurable FPGA-based systems, energy minimization in multi-mode real-time systems implemented on heterogeneous platforms, and codesign techniques for fault-tolerant systems.The solutions proposed in this thesis have been validated by extensive experiments, ranging from computer simulations to proof of concept implementations on real-life platforms. The results have confirmed the importance of the addressed aspects and the applicability of our techniques for design optimization of modern embedded systems. v vi Populärvetenskaplig Sammanfattning I dag är inbyggda system vanligt förekommande och deras antal fortsätter att öka. De används inom en mängd olika domäner, t.ex. hemelektronik, fordonsindustri, flygelektronik, medicin, etc., och de hittas nästan överallt omkring oss: från våra telefoner, bärbara datorer och tvättmaskiner till våra bilar. De applikationer som körs på dessa system har flera olika ökande krav: högprestanda, energieffektivitet, flexibilitet, feltolerans, realtidsegenskaper, och naturligtvis låg kostnad. För att kunna uppfylla dessa krav har industrin anammat arkitekturer som är mer och mer heterogena och som har omkonfigureringsmöjligheter. Olyckligtvis ökar detta komplexiteten när man ska utforma effektiva inbyggda system. I detta sammanhang blir det av yttersta betydelse att utveckla effektiva optimeringsmetoder och verktyg.Dagens applikationer består av en blandning av mjukvarukomponenter som har mycket olika energi-och prestandaegenskaper beroende på vilka hårdvaruenheter där de körs på, vilket gör dem lämpliga för heterogena plattformar. En heterogen plattform består av olika typer av hårdvaruen-heter, var och en med sina egenskaper, som riktar sig till vissa tillämpn-ingsområden. Under det senaste decenniet har utvecklingen av rekonfigurerbara hårdvarutekniker accelererat, vilket bidrar till den ökande populariteten för fältprogrammerbara grindmatriser (FPGA). Idag, ger hård-varutillverkare stöd för partiell dynamisk omkonfigurering; detta innebär att delar av en FPGA kan konfigureras vid run-time, medan andra delar förblir fullt fungerande. Dessa tekniska framsteg har...

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“…In our own work, we have investigated the challenges faced when augmenting multicore platforms with GPUs that have non-real-time, throughput-oriented, closedsource device drivers [15]. These drivers exhibit problematic behaviors for real-time systems.…”

Section: Introductionmentioning

confidence: 99%

Robust Real-Time Multiprocessor Interrupt Handling Motivated by GPUs

Elliott

Anderson

2012

2012 24th Euromicro Conference on Real-Time Systems

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Abstract-Architectures in which multicore chips are augmented with graphics processing units (GPUs) have great potential in many domains in which computationally intensive real-time workloads must be supported. However, unlike standard CPUs, GPUs are treated as I/O devices and require the use of interrupts to facilitate communication with CPUs. Given their disruptive nature, interrupts must be dealt with carefully in real-time systems. With GPU-driven interrupts, such disruptiveness is further compounded by the closed-source nature of GPU drivers. In this paper, such problems are considered and a solution is presented in the form of an extension to LITMUS RT called klmirqd. The design of klmirqd targets systems with multiple CPUs and GPUs. In such settings, interruptrelated issues arise that have not been previously addressed.

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Globally scheduled real-time multiprocessor systems with GPUs

Cited by 64 publications

References 19 publications

Warp-Based Load/Store Reordering to Improve GPU Time Predictability

Warp-Based Load/Store Reordering to Improve GPU Time Predictability

Hardware/Software Codesign of Embedded Systems with Reconfigurable and Heterogeneous Platforms

Robust Real-Time Multiprocessor Interrupt Handling Motivated by GPUs

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