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A novel, generic, framework for supporting self-organisation and self-management in hierarchical systems is presented. The framework allows for the incorporation of local self-organising and self-managing strategies at each level in the hierarchy. These local strategies determine the behaviour of that level and the effects of these strategies can be communicated to, and used by, the strategies in...
We propose methods to accelerate machine learning (ML) on sparse datasets with a distributed memory vector architecture. First, we propose a new communication method that reduces the amount of communication by exploiting the sparsity of the data. Second, we propose a new sparse matrix vector multiplication (SpMV) for a vector architecture, which often becomes the kernel operation of ML on sparse datasets...
The conventional OpenCL 1.x style CPU-GPU heterogeneous computing paradigm treats the CPU and GPU processors as loosely connected separate entities. At best each executes independent tasks, but, more commonly, the CPU idles while waiting for results from the GPU. No data-sharing and communications are allowed during kernel execution. This model limits the number of applications that can harness the...
The paper presents a method for parallel speculative query execution support to be applied in relational database systems. The method is based on dynamic analysis of input query stream in databases serviced in SQLite. A special representation of queries in the form of multigraphs is employed. A middleware called the Speculative Layer is introduced which determines the most promising speculative queries...
A promising approach to increase the efficiency of infrastructure usage is to adapt the assignment of resources to workloads. This can be used, for example, to consolidate existing workloads so that the new capability can be used to serve new requests, or alternatively unused resources may be turned off to reduce energy consumption. Many architectural solutions have been presented for data centre...
This paper proposes the concept of a multi-service cloud of drones that provides services required by people in crowded open air places, such as Internet connectivity or access to emergency services. The cloud of drones has the benefit of resource replication and tackling scalability. At the same time, their number and operation can be controlled by the cloud to enhance reliability and provide greater...
In the new Digital Economy, massive computer systems, often grouped in datacenters, serve as factories "producing" cloud services with massive consumption. However, to afford cloud services globally, we must address new research challenges in designing, operating, and using modern datacenters. We must also address challenges in educating and training the next generation of datacenter engineers...
Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
This paper investigates the scalability of WRF (Weather Research and Forecast) model on three different platforms: BlueGene/P, Intel Xeon Cluster and Microsoft Azure cloud at different resolutions and domain sizes. Contrary to prior work we benchmark the model on a cloud platform, analyze the behavior of various individual configurations, and test the scalability of our previously proposed parallel...
Gyrokinetic modeling is appropriate for describing plasma turbulence in the core of Tokamaks, and the gyroaverage operator is a cornerstone of this approach. In a gyrokinetic code the gyroaveraging scheme needs to be accurate enough, but also requires a low computational cost because it is often applied on the main unknown, namely the 5D guiding-center distribution function, as well as on several...
In this paper the authors compare the performance and scalability of the SHMEM and corresponding MPI-3 routines for five different benchmark tests using a Cray XC30. The performance of the MPI-3 get and put operations was evaluated using fence synchronization and also using lock-unlock synchronization. The five tests used communication patterns ranging from light to heavy data traffic: accessing distant...
Reproducibility of the execution of scientific applications on parallel and distributed systems is a growing interest, underlying the trustworthiness of the experiments and the conclusions derived from experiments. Dynamic loop scheduling (DLS) techniques are an effective approach towards performance improvement of scientific applications via load balancing. These techniques address algorithmic and...
Parallel applications are highly irregular and high performance computing (HPC) infrastructures are very complex. The HPC applications of interest herein are timestepping scientific applications (TSSA). Often, TSSA involve the repeated execution of multiple parallel loops with thousands of iterations and irregular behavior. Dynamic loop scheduling (DLS) techniques were developed over time and have...
Modern GPUs embrace on-chip cache memory to exploit the locality present in applications. However, the behavior and effect of the cache on GPUs are different from those on conventional processors due to the Single Instruction Multiple Thread (SIMT) thread execution model and resulting memory access patterns. Previous studies report that caching data can hurt the performance due to increased memory...
Although cloud computing greatly utilises virtualised environments for applications to be executed efficiently in low-cost hosting, it has turned energy wasting and overconsumption issues into major concerns. Cloud infrastructure is built on a great amount of server equipment, including high performance computing (HPC), and the servers are naturally prone to failures.In this paper, we report on an...
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