46,100 research outputs found
A Hierarchical Component-based WebGIS and Its Key Technologies
A practical hierarchical component-based WebGIS model referred to as Geo-Union is presented. Geo-Union consists of four layers: storage layer, service layer, component layer and application layer. Service layer is partitioned into another two layers: Geo-Union client and Geo-Union server. The architectures and object diagram of each layer in Geo-Union are discussed in details. After that, four key technologies adopted in Geo-Union (spatial data model, ORDB, spatial index and spatial cache) are summarized and analyzed, especially the spatial cache framework of Geo-Union. At last, some future works in WebGIS, such as interoperability, security, distributed computing and intelligent computing, are indicated and simply explored
Cache Equalizer: A Cache Pressure Aware Block Placement Scheme for Large-Scale Chip Multiprocessors
This paper describes Cache Equalizer (CE), a novel distributed cache management scheme for large scale chip multiprocessors (CMPs). Our work is motivated by large asymmetry in cache sets usages. CE decouples the physical locations of cache blocks from their addresses for the sake of reducing misses caused by destructive interferences. Temporal pressure at the on-chip last-level cache, is continuously collected at a group (comprised of cache sets) granularity, and periodically recorded at the memory controller to guide the placement process. An incoming block is consequently placed at a cache group that exhibits the minimum pressure. CE provides Quality of Service (QoS) by robustly offering better performance than the baseline shared NUCA cache. Simulation results using a full-system simulator demonstrate that CE outperforms shared NUCA caches by an average of 15.5% and by as much as 28.5% for the benchmark programs we examined. Furthermore, evaluations manifested the outperformance of CE versus related CMP cache designs
HVSTO: Efficient Privacy Preserving Hybrid Storage in Cloud Data Center
In cloud data center, shared storage with good management is a main structure
used for the storage of virtual machines (VM). In this paper, we proposed
Hybrid VM storage (HVSTO), a privacy preserving shared storage system designed
for the virtual machine storage in large-scale cloud data center. Unlike
traditional shared storage, HVSTO adopts a distributed structure to preserve
privacy of virtual machines, which are a threat in traditional centralized
structure. To improve the performance of I/O latency in this distributed
structure, we use a hybrid system to combine solid state disk and distributed
storage. From the evaluation of our demonstration system, HVSTO provides a
scalable and sufficient throughput for the platform as a service
infrastructure.Comment: 7 pages, 8 figures, in proceeding of The Second International
Workshop on Security and Privacy in Big Data (BigSecurity 2014
Memory bank predictors
Cache memories are commonly implemented through multiple memory banks to improve bandwidth and latency. The early knowledge of the data cache bank that an instruction will access can help to improve the performance in several ways. One scenario that is likely to become increasingly important is clustered microprocessors with a distributed cache. This work presents a study of different cache bank predictors. We show that effective bank predictors can be implemented with relatively low cost. For instance, a predictor of approximately 4 Kbytes is shown to achieve an average hit rate of 78% for SPECint2000 when used to predict accesses to an 8-bank cache memory in a contemporary superscalar processor. We also show how a predictor can be used to reduce the communication latency caused by memory accesses in a clustered microarchitecture with a distributed cache design.Peer ReviewedPostprint (published version
Cache-Aided Coded Multicast for Correlated Sources
The combination of edge caching and coded multicasting is a promising
approach to improve the efficiency of content delivery over cache-aided
networks. The global caching gain resulting from content overlap distributed
across the network in current solutions is limited due to the increasingly
personalized nature of the content consumed by users. In this paper, the
cache-aided coded multicast problem is generalized to account for the
correlation among the network content by formulating a source compression
problem with distributed side information. A correlation-aware achievable
scheme is proposed and an upper bound on its performance is derived. It is
shown that considerable load reductions can be achieved, compared to state of
the art correlation-unaware schemes, when caching and delivery phases
specifically account for the correlation among the content files.Comment: In proceeding of IEEE International Symposium on Turbo Codes and
Iterative Information Processing (ISTC), 201
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