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Most GPU-based graph systems cannot handle large-scale graphs that do not fit in the GPU memory. The ever-increasing graph size demands a scale-up graph system, which can run on a single GPU with optimized memory access efficiency and well-controlled data transfer overhead. However, existing systems either incur redundant data transfers or fail to use shared memory. In this paper we present Graphie,...
This paper presents the first systematic study on co-scheduling independent jobs on integrated CPU-GPU systems with power caps considered. It reveals the performance degradations caused by the co-run contentions at the levels of both memory and power. It then examines the problem of using job co-scheduling to alleviate the degradations in this less understood scenario. It offers several algorithms...
Modern GPUs feature complex memory system designs. One GPU may contain many types of memory of different properties. The best way to place data in memory is sensitive to many factors (e.g., program inputs, architectures), making portable optimizations of GPU data placement a difficult challenge. PORPLE is a recently proposed method that overcomes the difficulties by enabling online optimizations of...
The integrated architecture that features both CPU and GPU on the same die is an emerging and promising architecture for fine-grained CPU-GPU collaboration. However, the integration also brings forward several programming and system optimization challenges, especially for irregular applications. The complex interplay between heterogeneity and irregularity leads to very low processor utilization of...
We proposed a novel model to predict human's visual attention when free-viewing webpages. Compared with natural images, webpages are usually full of salient regions such as logos, text, and faces, while few of them attract human's attention in a short sight. Moreover, webpages perform distinct viewing patterns which are quite different from the natural images. In this paper, we introduced multi-features...
GPU is often equipped with complex memory systems, including globalmemory, texture memory, shared memory, constant memory, and variouslevels of cache. Where to place the data is important for theperformance of a GPU program. However, the decision is difficult for aprogrammer to make because of architecture complexity and thesensitivity of suitable data placements to input and architecturechanges.This...
To circumvent the limitation from the hardware scheduler on GPU, we create an SM-centric transformation technique. This technique enables complete control of the mapping between tasks and streaming multi-processors (SMs), and enables controlling the number of active thread blocks on each SM. Results show that our approach achieves better speedup than previous ones with kernel co-run cases.
The paper analyzes the traditional hook and inline hook's imperfection—easily to be detected and be recovered. To improve the inline hook technology, authors put forward a new technology called secret inline hook which has greater confidentiality and can avoid the malware's detection and falsify effectively. The technology has been successfully applied to the automatic analysis system of malware behaviour...
Face recognition plays a important role in computer vision. Recent researches show that high dimensional face images lie on or close to a low dimensional manifold. LPP is a widely used manifold reduced dimensionality technique. But it suffers two problem: (1) Small Sample Size problem; (2)the performance is sensitive to the neighborhood size k. In order to address the problems, this paper proposed...
This paper presents a genetic algorithm (GA) approach for parameters optimization of support vector machine, which is used for the object-oriented classification of high spatial resolution images over urban area. The proposed method is a three-step routine involves the integration of 1) image segmentation, 2) GA-based parameter optimization of Support vector machine (SVM), and 3) objected-based classification...
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