Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 38 for “"Graph Analytics"”.
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Graph analytics on relational databases
Graph analytics has become increasing popular in the recent years. Conventionally, data is stored in relational databases that have been refined over decades, resulting in highly optimized data processing engines. However, the awkwardness of expressing iterative queries in SQL makes the relational …
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Graph Analytics with Data Science Languages
In Big Data analytics, data exploded in the three Vs: Volume, Velocity, and Variety. The three Vs brought new challenges to data analysis systems, which require new approaches, tools, and algorithms to analyze data. The most complex exploration mechanism in Big Data Analytics is graphs, which are …
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High Performance Large Graph Analytics by Enhancing Locality
<p>Graphs are widely used in a variety of domains for representing entities and their relationship to each other. Graph analytics helps to understand, detect, extract and visualize insightful relationships between different entities. Graph analytics has a wide range of applications in various …
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Systems and Techniques for Efficient Real-World Graph Analytics
Graphs are a natural way to model real-world entities and relationships between them, ranging from social networks and biological datasets to cloud computing infrastructure data lineage graphs. Queries over these large graphs often involve expensive subgraph traversals and complex analytical …
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The GraphGrind Framework: Fast Graph Analytics on Large Shared-Memory Systems
… they provide an opportunity to perform efficient graph analytics on a single machine. Graph analytics is characterised by frequent synchronisation, which is addressed in part by shared memory systems. However, performance is limited by load imbalance and poor memory locality, which originate in …
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Domain-specific adaptation of large language models and integration with knowledge graph analytics for enhanced bridge maintenance decision making
… a novel large language model (LLM)-based analytics framework for bridge data integration and enhanced maintenance decision support is proposed. The proposed framework is composed of six primary components: (1) an LLM-based semantic information extraction method for extracting information …
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Image alignment and dynamic graph analytics : two case studies of how managing data movement can make (parallel) code run fast
… cluster. The second case study explores dynamic graph analytics, where I describe the design of a new data structure for storing dynamic graphs that matches the performance of standard, static formats and enables high performance, dynamic operations achieving millions of updates per second.
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Accelerating graph computation with system optimizations and algorithmic design
… data in today's world can be represented in a graph form, and these graphs can then be used as input to graph applications to derive useful information, such as shortest paths in a road network, similarity between drugs in a drug-protein network, persons of interest in a social network, or …
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A Reconfigurable, Distributed-Memory Accelerator for Sparse Applications
… at the heart of many scientific computing and graph analytics algorithms. On conventional systems, their irregular memory accesses and low arithmetic intensity create challenging memory bandwidth bottlenecks. To overcome such bottlenecks, distributed-SRAM architectures use tiled arrays of …
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Improving performance and security of indirect memory references on speculative execution machines
… as in-memory databases, machine learning, and graph analytics. While terabytes of DRAM are now available in public cloud machines, indirect memory references in large working sets often incur the full penalty of a random DRAM access. Furthermore, caches and speculative execution enable the …
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Intelligent scheduling for simultaneous CPU-GPU applications
… specialized accelerators has emerged recently. Graphics processing unit (GPU) is the most widely used accelerator. To fully utilize such a heterogeneous system’s full computing power, coordination between the two distinct devices, CPU and GPU, is necessary. Previous research has addressed this …
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Weld : fast data-parallel computation on modern hardware
… common data-parallel applications (e.g., SQL, graph analytics and machine learning) while being easy to parallelize on modern hardware, through the use of a simple "parallel builder" abstraction and nested parallel loops. Weld supports complex optimizations like vectorization and loop blocking, …
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Storage and processing systems for power-law graphs
Large graphs abound around us - online social networks, Web graphs, the Internet, citation networks, protein interaction networks, telephone call graphs, peer-to-peer overlay networks, electric power grid networks, etc. Many real- life graphs are power-law graphs. A fundamental challenge in today’s …
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Memory access patterns and page promotion in hybrid memory systems
… the resurgence of machine learning, big data, graph analytics, and database management systems, especially in modern datacenters. In addition to the massive data that these applications process, they exhibit varying and non-deterministic memory access patterns making I/O latency a prime …
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Spatial and Temporal Topological Analysis of Landscape Structure using Graph Theory
… 2) outlines a new data structure based on graph theory. The Spatio-Temporal Relational Graph (STRG) is created to record spatial phenomena through space and time. STRG has the advantage of being an extension of mainstream spatial data structures that can be easily applied to existing …
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High performance DFS-based subgraph enumeration on GPUs
Subgraph enumeration is an important problem in the field of Graph Analytics with numerous applications. The problem is provably NP-complete and requires sophisticated heuristics and highly efficient implementations to be feasible on problem sizes of realistic scales. Parallel solutions have shown …
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Architectural Support for Effective Data Compression In Irregular Applications
Irregular applications, such as graph analytics and sparse linear algebra, exhibit frequent indirect, data-dependent accesses to single or short sequences of elements that cause high main memory traffic and limit performance. Data compression is a promising way to accelerate irregular applications …
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Exploiting cost-performance tradeoffs for modern cloud systems
… As another example, run-time performance of graph analytics jobs sharing a multi-tenant cluster can be made better by trading of the cost of replication of the input graph data-set stored in the associated distributed file system. Today cloud system providers have to manually tune the system …
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EVIDENCE EVALUATION IN BIOMEDICAL KNOWLEDGE GRAPHS FOR PHARMACEUTICAL DISCOVERY
… and query biomedical heterogeneous knowledge graphs in a computational discovery platform guided by rational, algorithmic measures of relevance and confidence, facilitating scientific discovery? And, how have continuing waves of scientific and technological progress informed and empowered …
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Characterization of containers in emerging applications: Microservices, FAAS and GPUS
… center use cases with databases, web servers, graph analytics, Functions-as-a-Service, and GPU-accelerated stencil, lower-upper decomposition, object tracking and neural network applications. Furthermore, this thesis analyzes Docker Engine performance by bringing up containers and breaks down …
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