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Mainstream indoor localization technologies rely on RF signatures that require extensive human efforts to measure and periodically recalibrate signatures. The progress to ubiquitous localization remains slow. In this study, we explore Sextant, an alternative approach that leverages environmental reference objects such as store logos. A user uses a smartphone to obtain relative position measurements...
Dynamic community detection algorithms tryto solve problems that identify communities of dynamicnetwork which consists of a series of network snapshots. Toaddress this issue, here we propose a new dynamiccommunity detection algorithm based on incrementalidentification according to a vertex-based metric calledpermanence. We incrementally analyze the communityownership of partial vertices, so as to...
Optimizing programs for Graphic Processing Unit (GPU) requires thorough knowledge about the values of architectural features for the new computing platform. However, this knowledge is frequently unavailable, e.g., due to insufficient documentation, which is probably a result of the infancy of general purpose computing on the GPU. What makes the modeling of program performance on GPU even more difficult...
The LRU-like algorithm was proposed for the block management to enhance the direct-mapped cache scheme. Base on the LRU-like algorithm, the Least-Recently-Used Block Filtering cache (LBF cache), which can filter LRU blocks, is designed. From the point of cache usage rate, the LBF cache uses LRU-like algorithm to allocate and replace blocks, and evicts the blocks whose usage shows the least efficiency...
A program segment such as a function or a basic block sequence may display different behaviors during the execution of the program. For example, a basic block sequence may consistently show few cache misses during the first 10 times it is executed, while the same basic block sequence may experience high number of cache misses when the sequence is invoked in the next 100 times. The divergence within...
Modern GPUs open a completely new field to optimize embarrassingly parallel algorithms. Implementing an algorithm on a GPU confronts the programmer with a new set of challenges for program optimization. Some of the most notable ones are isolating the part of the algorithm that can be optimized to run on the GPU; tuning the program for the GPU memory hierarchy whose organization and performance implications...
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