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GraphScope Flex: LEGO-like Graph Computing Stack
Furthermore, GraphScope Flex accomplishes up to a 2, 400X performance gain in real-world applications, demonstrating its proficiency across a wide range of graph computing scenarios with increased effectiveness.
Distributed, Parallel, and Cluster Computing Databases
Gunrock: GPU Graph Analytics
For large-scale graph analytics on the GPU, the irregularity of data access and control flow, and the complexity of programming GPUs, have presented two significant challenges to developing a programmable high-performance graph library.
Distributed, Parallel, and Cluster Computing
Stateful Dataflow Multigraphs: A Data-Centric Model for High-Performance Parallel Programs
With the ubiquity of accelerators, such as FPGAs and GPUs, the complexity of high-performance programming is increasing beyond the skill-set of the average scientist in domains outside of computer science.
Programming Languages Distributed, Parallel, and Cluster Computing Performance
Neural Architecture Search with Bayesian Optimisation and Optimal Transport
A common use case for BO in machine learning is model selection, where it is not possible to analytically model the generalisation performance of a statistical model, and we resort to noisy and expensive training and validation procedures to choose the best model.
GraphBolt: Dependency-Driven Synchronous Processing of Streaming Graphs
Efficient streaming graph processing systems leverage incremental processing by updating computed results to reflect the change in graph structure for the latest graph snapshot.
SuperNOVA: Design Strategies and Opportunities for Interactive Visualization in Computational Notebooks
Through this study, we identify key design implications and trade-offs, such as leveraging multimodal data in notebooks as well as balancing the degree of visualization-notebook integration.
The Noir Dataflow Platform: Efficient Data Processing without Complexity
This demands for software platforms that offer simple programming abstractions to express data analysis tasks and that can execute them in an efficient and scalable way.
Distributed, Parallel, and Cluster Computing
Kerncraft: A Tool for Analytic Performance Modeling of Loop Kernels
We then present Kerncraft, a tool that can automatically construct Roofline and ECM models for loop nests by performing the required code, data transfer, and LC analysis.
Performance
Dodona: learn to code with a virtual co-teacher that supports active learning
Dodona (dodona. ugent. be) is an intelligent tutoring system for computer programming.
Computers and Society
Multi-Component Optimization and Efficient Deployment of Neural-Networks on Resource-Constrained IoT Hardware
The majority of IoT devices like smartwatches, smart plugs, HVAC controllers, etc., are powered by hardware with a constrained specification (low memory, clock speed and processor) which is insufficient to accommodate and execute large, high-quality models.
