1,228 research outputs found
VegaProf: Profiling Vega Visualizations
Vega is a popular domain-specific language (DSL) for visualization
specification. At runtime, Vega's DSL is first transformed into a dataflow
graph and then functions to render visualization primitives. While the Vega
abstraction of implementation details simplifies visualization creation, it
also makes Vega visualizations challenging to debug and profile without
adequate tools. Our formative interviews with three practitioners at Sigma
Computing showed that existing developer tools are not suited for visualization
profiling as they are disconnected from the semantics of the Vega DSL
specification and its resulting dataflow graph. We introduce VegaProf, the
first performance profiler for Vega visualizations. VegaProf effectively
instruments the Vega library by associating the declarative specification with
its compilation and execution. Using interactive visualizations, VegaProf
enables visualization engineers to interactively profile visualization
performance at three abstraction levels: function, dataflow graph, and
visualization specification. Our evaluation through two use cases and feedback
from five visualization engineers at Sigma Computing shows that VegaProf makes
visualization profiling tractable and actionable.Comment: Submitted to EuroVis'2
Live Programming Environment for Deep Learning with Instant and Editable Neural Network Visualization
Artificial intelligence (AI) such as deep learning has achieved significant success in a variety of application domains. Several visualization techniques have been proposed for understanding the overall behavior of the neural network defined by deep learning code. However, they show visualization only after the code or network definition is written and it remains complicated and unfriendly for newbies to build deep neural network models on a code editor. In this paper, to help user better understand the behavior of networks, we augment a code editor with instant and editable visualization of network model, inspired by live programming which provides continuous feedback to the programmer
A File System Abstraction for Sense and Respond Systems
The heterogeneity and resource constraints of sense-and-respond systems pose
significant challenges to system and application development. In this paper, we
present a flexible, intuitive file system abstraction for organizing and
managing sense-and-respond systems based on the Plan 9 design principles. A key
feature of this abstraction is the ability to support multiple views of the
system via filesystem namespaces. Constructed logical views present an
application-specific representation of the network, thus enabling high-level
programming of the network. Concurrently, structural views of the network
enable resource-efficient planning and execution of tasks. We present and
motivate the design using several examples, outline research challenges and our
research plan to address them, and describe the current state of
implementation.Comment: 6 pages, 3 figures Workshop on End-to-End, Sense-and-Respond Systems,
Applications, and Services In conjunction with MobiSys '0
LEGaTO: first steps towards energy-efficient toolset for heterogeneous computing
LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC.Peer ReviewedPostprint (author's final draft
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