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DOI: 10.4230/OASIcs.Fog-IoT.2020.4

Processing LiDAR Data from a Virtual Logistics Space

Authors: Jaakko Harjuhahto, Anton Debner, and Vesa Hirvisalo

Published in: OASIcs, Volume 80, 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)

Abstract

We study computing solutions that can be used close to the network edge in I2oT systems (Industrial Internet of Things). As a specific use case, we consider a factory warehouse with AGVs (Automated Guided Vehicles). The computing services for such systems should be dependable, yield high performance, and have low latency. For understanding such systems, we have constructed a hybrid system that consists of a simulator yielding virtual LiDAR sensor data streams in real-time and a sensor data processor on a real cluster that acts as a fog computing node close to the warehouse. The processing merges the observations done from the individual sensor streams without using the vehicle-to-vehicle communication links for the complicated computing. We present our experimental results, which show the feasibility of the computing solution.

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Jaakko Harjuhahto, Anton Debner, and Vesa Hirvisalo. Processing LiDAR Data from a Virtual Logistics Space. In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 4:1-4:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{harjuhahto_et_al:OASIcs.Fog-IoT.2020.4,
  author =	{Harjuhahto, Jaakko and Debner, Anton and Hirvisalo, Vesa},
  title =	{{Processing LiDAR Data from a Virtual Logistics Space}},
  booktitle =	{2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
  pages =	{4:1--4:12},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-144-3},
  ISSN =	{2190-6807},
  year =	{2020},
  volume =	{80},
  editor =	{Cervin, Anton and Yang, Yang},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020.4},
  URN =		{urn:nbn:de:0030-drops-119985},
  doi =		{10.4230/OASIcs.Fog-IoT.2020.4},
  annote =	{Keywords: simulation, hybrid systems, new control applications, fog computing}
}

Document

DOI: 10.4230/OASIcs.WCET.2014.43

On Static Timing Analysis of GPU Kernels

Authors: Vesa Hirvisalo

Published in: OASIcs, Volume 39, 14th International Workshop on Worst-Case Execution Time Analysis (2014)

Abstract

We study static timing analysis of programs running on GPU accelerators. Such programs follow a data parallel programming model that allows massive parallelism on manycore processors. Data parallel programming and GPUs as accelerators have received wide use during the recent years. The timing analysis of programs running on single core machines is well known and applied also in practice. However for multicore and manycore machines, timing analysis presents a significant but yet not properly solved problem. In this paper, we present static timing analysis of GPU kernels based on a method that we call abstract CTA simulation. Cooperative Thread Arrays (CTA) are the basic execution structure that GPU devices use in their operation that proceeds in thread groups called warps. Abstract CTA simulation is based on static analysis of thread divergence in warps and their abstract scheduling.

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Vesa Hirvisalo. On Static Timing Analysis of GPU Kernels. In 14th International Workshop on Worst-Case Execution Time Analysis. Open Access Series in Informatics (OASIcs), Volume 39, pp. 43-52, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

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@InProceedings{hirvisalo:OASIcs.WCET.2014.43,
  author =	{Hirvisalo, Vesa},
  title =	{{On Static Timing Analysis of GPU Kernels}},
  booktitle =	{14th International Workshop on Worst-Case Execution Time Analysis},
  pages =	{43--52},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-69-9},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{39},
  editor =	{Falk, Heiko},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.WCET.2014.43},
  URN =		{urn:nbn:de:0030-drops-46033},
  doi =		{10.4230/OASIcs.WCET.2014.43},
  annote =	{Keywords: Parallelism, WCET}
}

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Documents authored by Hirvisalo, Vesa

Processing LiDAR Data from a Virtual Logistics Space

Abstract

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On Static Timing Analysis of GPU Kernels

Abstract

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