Programming bsp and multi-bsp algorithms in ml

Allombert, Victor; Gava, Frédéric

doi:10.1007/s11227-019-02822-9

Cited by 3 publications

(8 citation statements)

References 23 publications

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“…An important issue [1,26] is the ability of designing immortal algorithms, which are algorithms that scale for any machine in the present and in the future as long as the bridging model can be adapted to it. In particular, these algorithms must work for any number of computing units (up to some constraints such as a number of processors equal to a power of two).…”

Section: Multi-processors Algorithms and Hierarchical Architecturesmentioning

confidence: 99%

“…This also simplifies the presentation. Thirdly, we natively allow horizontal communications to make the set of the bsp algorithms a subset of the multi-bsp ones and, in particular, with the idea of working in an incremental manner (as in [1]), that is using bsp programs inside multi-bsp ones. Q5: So your model do not have shared memories and concurrent accesses to them?…”

Section: Q3: and What About The Execution Model Of Multi-bsp Algorithms?mentioning

confidence: 99%

“…It is the responsibility of the communication function to (implicitly) perform such computations because it is oracular. In "practice" [1,30], the needed computations that are done in the upper memories focus on data management and one selected (by the implementation/architecture) processor of a branch can do such a work. We will discuss this issue later.…”

Section: Which Performs the Communications Of The Memories Of A Componentmentioning

confidence: 99%

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Axiomatization and Imperative Characterization of Multi-BSP Algorithms: A Q&A on a Partial Solution

Gava

Marquer

2020

Int J Parallel Prog

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multi-bsp is a new bridging model which takes into account hierarchical architectures. We discuss two questions about multi-bsp algorithms and their programming: (1) How do we get a formal characterization of the class of multi-bsp algorithms? (2) How can a programming language be proven algorithmically complete for such a class? Our solution is based on an extension of a bsp version of sequential abstract state machines (asms).

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Section: Multi-processors Algorithms and Hierarchical Architecturesmentioning

confidence: 99%

Section: Q3: and What About The Execution Model Of Multi-bsp Algorithms?mentioning

confidence: 99%

Section: Which Performs the Communications Of The Memories Of A Componentmentioning

confidence: 99%

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Axiomatization and Imperative Characterization of Multi-BSP Algorithms: A Q&A on a Partial Solution

Gava

Marquer

2020

Int J Parallel Prog

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“…For the Shared storage mode, the remote read operation will be deemed as two messages passing, and the influence of pipeline prefetching technology, cache-induced data inconsistency and Cache hit ratio on the calculation is not considered, which will bring data deviation to the system designed in this paper. In the present work, the BSP model (Allombert & Gava, 2020;Liu et al, 2020;Marquer & Gava, 2019) adopts obstacle synchronization mode to realize global synchronization by hardware, thus providing an effective way to execute tightly coupled synchronous parallel algorithm, and it's adopted to divide m supersteps into m EV, which can effectively avoid the deadlock phenomenon.The fence can be synchronized according to the different lengths of the three signals in each superstep.…”

Section: Introductionmentioning

confidence: 99%

Electric vehicle regional management system based on the BSP model and multi-information fusion

Zeng

Sun

2020

Systems Science & Control Engineering

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Aiming at the problem of most electric vehicles (EV) sounding false alarms due to touches, an EV alarm regionalization management control system based on multi-information fusion and the BSP model is designed in the present study. The proposed system uses multiple sensors to detect the state of the EV, and realizes multi-sensor information fusion by the Lagrange interpolation method. The ZigBee networking technology is used to carry out the regional management of EV alarms, establish a BSP model, realize the synchronous transmission of system status detection signals, and finally complete the alarm function. The experimental results show that the false alarm rate of traditional EV alarm systems is about 85.5%, that of alarm systems that perform state monitoring without information fusion is about 11.3%, and that of the proposed alarm system that performs multi-information fusion simultaneously is greatly reduced to about 0.5%.

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“…These apparent trophic cascades can operate through top-down and bottom-up forces (Kagata and Ohgushi 2006) and can have profound effects on ecosystem structure and function (Hebblewhite et al 2005, Ripple et al 2014. In temperate systems, anthropogenically elevated herbivore populations can initiate these cascades, altering songbird (Allombert et al 2005a, Martin et al 2011) and invertebrate (Allombert et al 2005b) communities through changes to vegetation structure. Arctic systems are less complex (Gauthier et al 2011, Legagneux et al 2012, highly connected (Wirta et al 2015), and experiencing rapid environmental change (Post et al 2009, Collins et al 2013, potentially leaving them more susceptible to herbivore-induced trophic cascades.…”

Section: Introductionmentioning

confidence: 99%

Broad‐scale changes in tundra‐nesting bird abundance in response to hyperabundant geese

et al. 2019

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Environmental changes can propagate through food webs in complex ways via trophic cascades. In the North American Arctic, hyperabundant populations of geese are causing significant habitat change and the resulting trophic cascades are known to impact plant and invertebrate communities. However, the potential impacts on other tundra‐nesting birds are not fully understood. Here, we evaluate the impacts of light geese (Snow Geese, Chen caerulescens, and Ross’ Goose, Chen rossii) populations on other tundra‐nesting birds, using count data collected during bird surveys conducted at varying distances from light goose colonies across the Canadian Arctic. From a dataset of 920 12–16 ha plots distributed across the Canadian Arctic, we identified 527 that were within 200 km of the mapped extent of known light goose colonies. After accounting for regional variation, we demonstrate that densities of most Cover‐Nesting Shorebirds and passerines are depressed in the vicinity of light goose colonies. We suggest that these trends are the results of the combined effects of goose‐induced changes in habitat and predator–prey interactions. These direct and indirect effects of light geese could be contributing to the declines experienced by some tundra‐nesting bird populations in parts of their range. Ongoing climate‐related changes to habitat, predators, and arthropods could interact with this effect of geese to further alter the suitability of tundra habitats for Arctic‐breeding birds, in additive or even unanticipated ways.

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Programming bsp and multi-bsp algorithms in ml

Cited by 3 publications

References 23 publications

Axiomatization and Imperative Characterization of Multi-BSP Algorithms: A Q&A on a Partial Solution

Axiomatization and Imperative Characterization of Multi-BSP Algorithms: A Q&A on a Partial Solution

Electric vehicle regional management system based on the BSP model and multi-information fusion

Broad‐scale changes in tundra‐nesting bird abundance in response to hyperabundant geese

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