8,242 research outputs found
Resource-aware scheduling for 2D/3D multi-/many-core processor-memory systems
This dissertation addresses the complexities of 2D/3D multi-/many-core processor-memory systems, focusing on two key areas: enhancing timing predictability in real-time multi-core processors and optimizing performance within thermal constraints. The integration of an increasing number of transistors into compact chip designs, while boosting computational capacity, presents challenges in resource contention and thermal management. The first part of the thesis improves timing predictability. We enhance shared cache interference analysis for set-associative caches, advancing the calculation of Worst-Case Execution Time (WCET). This development enables accurate assessment of cache interference and the effectiveness of partitioned schedulers in real-world scenarios. We introduce TCPS, a novel task and cache-aware partitioned scheduler that optimizes cache partitioning based on task-specific WCET sensitivity, leading to improved schedulability and predictability. Our research explores various cache and scheduling configurations, providing insights into their performance trade-offs. The second part focuses on thermal management in 2D/3D many-core systems. Recognizing the limitations of Dynamic Voltage and Frequency Scaling (DVFS) in S-NUCA many-core processors, we propose synchronous thread migrations as a thermal management strategy. This approach culminates in the HotPotato scheduler, which balances performance and thermal safety. We also introduce 3D-TTP, a transient temperature-aware power budgeting strategy for 3D-stacked systems, reducing the need for Dynamic Thermal Management (DTM) activation. Finally, we present 3QUTM, a novel method for 3D-stacked systems that combines core DVFS and memory bank Low Power Modes with a learning algorithm, optimizing response times within thermal limits. This research contributes significantly to enhancing performance and thermal management in advanced processor-memory systems
A Survey of Prediction and Classification Techniques in Multicore Processor Systems
In multicore processor systems, being able to accurately predict the future provides new optimization opportunities, which otherwise could not be exploited. For example, an oracle able to predict a certain application\u27s behavior running on a smart phone could direct the power manager to switch to appropriate dynamic voltage and frequency scaling modes that would guarantee minimum levels of desired performance while saving energy consumption and thereby prolonging battery life. Using predictions enables systems to become proactive rather than continue to operate in a reactive manner. This prediction-based proactive approach has become increasingly popular in the design and optimization of integrated circuits and of multicore processor systems. Prediction transforms from simple forecasting to sophisticated machine learning based prediction and classification that learns from existing data, employs data mining, and predicts future behavior. This can be exploited by novel optimization techniques that can span across all layers of the computing stack. In this survey paper, we present a discussion of the most popular techniques on prediction and classification in the general context of computing systems with emphasis on multicore processors. The paper is far from comprehensive, but, it will help the reader interested in employing prediction in optimization of multicore processor systems
Temperature Regulation in Multicore Processors Using Adjustable-Gain Integral Controllers
This paper considers the problem of temperature regulation in multicore
processors by dynamic voltage-frequency scaling. We propose a feedback law that
is based on an integral controller with adjustable gain, designed for fast
tracking convergence in the face of model uncertainties, time-varying plants,
and tight computing-timing constraints. Moreover, unlike prior works we
consider a nonlinear, time-varying plant model that trades off precision for
simple and efficient on-line computations. Cycle-level, full system simulator
implementation and evaluation illustrates fast and accurate tracking of given
temperature reference values, and compares favorably with fixed-gain
controllers.Comment: 8 pages, 6 figures, IEEE Conference on Control Applications 2015,
Accepted Versio
CoMeT: An Integrated Interval Thermal Simulation Toolchain for 2D, 2.5 D, and 3D Processor-Memory Systems
Processing cores and the accompanying main memory working in tandem enable
the modern processors. Dissipating heat produced from computation, memory
access remains a significant problem for processors. Therefore, processor
thermal management continues to be an active research topic. Most thermal
management research takes place using simulations, given the challenges of
measuring temperature in real processors. Since core and memory are fabricated
on separate packages in most existing processors, with the memory having lower
power densities, thermal management research in processors has primarily
focused on the cores.
Memory bandwidth limitations associated with 2D processors lead to
high-density 2.5D and 3D packaging technology. 2.5D packaging places cores and
memory on the same package. 3D packaging technology takes it further by
stacking layers of memory on the top of cores themselves. Such packagings
significantly increase the power density, making processors prone to heating.
Therefore, mitigating thermal issues in high-density processors (packaged with
stacked memory) becomes an even more pressing problem. However, given the lack
of thermal modeling for memories in existing interval thermal simulation
toolchains, they are unsuitable for studying thermal management for
high-density processors.
To address this issue, we present CoMeT, the first integrated Core and Memory
interval Thermal simulation toolchain. CoMeT comprehensively supports thermal
simulation of high- and low-density processors corresponding to four different
core-memory configurations - off-chip DDR memory, off-chip 3D memory, 2.5D, and
3D. CoMeT supports several novel features that facilitate overlying system
research. Compared to an equivalent state-of-the-art core-only toolchain, CoMeT
adds only a ~5% simulation-time overhead. The source code of CoMeT has been
made open for public use under the MIT license.Comment: https://github.com/marg-tools/CoMe
Radiation safety based on the sky shine effect in reactor
In the reactor operation, neutrons and gamma rays are the most dominant radiation.
As protection, lead and concrete shields are built around the reactor. However, the radiation
can penetrate the water shielding inside the reactor pool. This incident leads to the occurrence
of sky shine where a physical phenomenon of nuclear radiation sources was transmitted
panoramic that extends to the environment. The effect of this phenomenon is caused by the
fallout radiation into the surrounding area which causes the radiation dose to increase. High
doses of exposure cause a person to have stochastic effects or deterministic effects. Therefore,
this study was conducted to measure the radiation dose from sky shine effect that scattered
around the reactor at different distances and different height above the reactor platform. In this
paper, the analysis of the radiation dose of sky shine effect was measured using the
experimental metho
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