TSIC: Thermal Scheduling Simulator for Chip Multiprocessors

Stavrou, Kyriakos; Trancoso, Pedro

doi:10.1007/11573036_56

Cited by 12 publications

(8 citation statements)

References 9 publications

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“…A design of a thermal-aware scheduler has been recently proposed. (12,13) In an extreme case, cores may be shut down altogether (14) in order to cool down a certain area or the overall chip. Notice that even in the extreme case, the user would not be dramatically affected as applications will still execute normally but on a smaller number of cores.…”

Section: Chip Multiprocessormentioning

confidence: 99%

A Case for Chip Multiprocessors Based on the Data-Driven Multithreading Model

Trancoso

Evripidou

Stavrou

et al. 2006

Int J Parallel Prog

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Current high-end microprocessors achieve high performance as a result of adding more features and therefore increasing complexity. This paper makes the case for a Chip-Multiprocessor based on the Data-Driven Multithreading (DDM-CMP) execution model in order to overcome the limitations of current design trends. Data-Driven Multithreading (DDM) is a multithreading model that effectively hides the communication delay and synchronization overheads. DDM-CMP avoids the complexity of other designs by combining simple commodity microprocessors with a small hardware overhead for thread scheduling and an interconnection network. Preliminary experimental results show that a DDM-CMP chip of the same hardware budget as a highend commercial microprocessor, clocked at the same frequency, achieves a speedup of up to 18.5 with a 78-81% power consumption of the commercial chip. Overall, the estimated results for the proposed DDM-CMP architecture show a significant benefit in terms of both speedup and power consumption making it an attractive architecture for future processors.

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Section: Chip Multiprocessormentioning

confidence: 99%

A Case for Chip Multiprocessors Based on the Data-Driven Multithreading Model

Trancoso

Evripidou

Stavrou

et al. 2006

Int J Parallel Prog

Self Cite

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“…From an engineering perspective, knowledge of a surface geometry that maximizes the transport rate offers opportunities for new designs that exhibit enhanced characteristics and properties. For example, the problem of transport across an uneven surface, described in the preceding paragraph, is relevant to a variety of engineering applications involving heat transfer across rough and irregular boundaries, such as the surface of a circuit board in microelectronics [22,23,24,25]. In general, heat transfer in slab-like configurations is of interest to problems associated with Heat Transport from Extended Surfaces (Fins) [8] and inverted high conductivity fins/inserts [26].…”

Section: Introductionmentioning

confidence: 99%

Critical thickness of an optimum extended surface characterized by uniform heat transfer coefficient

Leontiou¹,

Fyrillas²

2015

Preprint

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We consider the heat transfer problem associated with a periodic array of extended surfaces (fins) subjected to convection heat transfer with a uniform heat transfer coefficient. Our analysis differs from the classical approach as (i) we consider two-dimensional heat conduction and (ii) the base of the fin is included in the heat transfer process. The problem is modeled as an arbitrary two-dimensional channel whose upper surface is flat and isothermal, while the lower surface has a periodic array of extensions/fins which are subjected to heat convection with a uniform heat transfer coefficient. Using the generalized Schwarz-Christoffel transformation the domain is mapped onto a straight channel where the heat conduction problem is solved using the boundary element method. The boundary element solution is subsequently used to pose a shape optimization problem, i.e. an inverse problem, where the objective function is the normalized Shape Factor and the variables of the optimization are the parameters of the Schwarz-Christoffel transformation. Numerical optimization suggests that the optimum fin is infinitely thin and that there exists a critical Biot number that characterizes whether the addition of the fin would result in an enhancement of heat transfer. The existence of a critical Biot number was investigated for the case of rectangular fins. It is concluded that a rectangular fin is effective if its thickness is less than 1.64 k/h, where the h is the heat transfer coefficient and k is the thermal conductivity. This result is independent of both the thickness of the base and the length of the fin.

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“…• Techniques such as, TSIC [65], TEMPEST [60] and PDTM [71] use an empirical thermal model to simulate the heat exchange between adjacent cores.…”

Section: Discussionmentioning

confidence: 99%

“…where is the thermal capacitance of node , is node temperature as a function of the time , denotes the instantaneous power input at node , ℎ is the set of all The model proposed in [65] improves the computation efficiency for temperature evaluation so as to be applicable for the online scenario. However, the model uses a time-driven approach which is only suitable for small-interval updates, using very fine granularity scheduling.…”

Section: Power/thermal Modelmentioning

confidence: 99%

“…Secondly, the accuracy of ABTM heavily depends on the training task set. Lastly, CBTM is not accurate as the simplified exponential thermal model cannot be applied in a multi-core scenario due to inter-core thermal coupling[92][65].DTAS is a relatively new research topic, with little in common with the more mature DTM policies. Each of the DTAS techniques in the three categories have some weaknesses: 1) Look-current techniques (e.g.…”

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confidence: 99%

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High level thermal-aware scheduling for multiprocessors

Cui¹

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TSIC: Thermal Scheduling Simulator for Chip Multiprocessors

Cited by 12 publications

References 9 publications

A Case for Chip Multiprocessors Based on the Data-Driven Multithreading Model

A Case for Chip Multiprocessors Based on the Data-Driven Multithreading Model

Critical thickness of an optimum extended surface characterized by uniform heat transfer coefficient

High level thermal-aware scheduling for multiprocessors

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