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Documents authored by Yun, Heechul

Document
DOI: 10.4230/LIPIcs.ECRTS.2019.17
Impact of DM-LRU on WCET: A Static Analysis Approach

Authors: Renato Mancuso, Heechul Yun, and Isabelle Puaut

Published in: LIPIcs, Volume 133, 31st Euromicro Conference on Real-Time Systems (ECRTS 2019)

Abstract
Cache memories in modern embedded processors are known to improve average memory access performance. Unfortunately, they are also known to represent a major source of unpredictability for hard real-time workload. One of the main limitations of typical caches is that content selection and replacement is entirely performed in hardware. As such, it is hard to control the cache behavior in software to favor caching of blocks that are known to have an impact on an application’s worst-case execution time (WCET). In this paper, we consider a cache replacement policy, namely DM-LRU, that allows system designers to prioritize caching of memory blocks that are known to have an important impact on an application’s WCET. Considering a single-core, single-level cache hierarchy, we describe an abstract interpretation-based timing analysis for DM-LRU. We implement the proposed analysis in a self-contained toolkit and study its qualitative properties on a set of representative benchmarks. Apart from being useful to compute the WCET when DM-LRU or similar policies are used, the proposed analysis can allow designers to perform WCET impact-aware selection of content to be retained in cache.
Cite as

Renato Mancuso, Heechul Yun, and Isabelle Puaut. Impact of DM-LRU on WCET: A Static Analysis Approach. In 31st Euromicro Conference on Real-Time Systems (ECRTS 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 133, pp. 17:1-17:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{mancuso_et_al:LIPIcs.ECRTS.2019.17,
  author =	{Mancuso, Renato and Yun, Heechul and Puaut, Isabelle},
  title =	{{Impact of DM-LRU on WCET: A Static Analysis Approach}},
  booktitle =	{31st Euromicro Conference on Real-Time Systems (ECRTS 2019)},
  pages =	{17:1--17:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-110-8},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{133},
  editor =	{Quinton, Sophie},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2019.17},
  URN =		{urn:nbn:de:0030-drops-107546},
  doi =		{10.4230/LIPIcs.ECRTS.2019.17},
  annote =	{Keywords: real-time, static cache analysis, abstract interpretation, LRU, deterministic memory, static cache locking, dynamic cache locking, cache profiling, WCET analysis}
}
Document
DOI: 10.4230/LIPIcs.ECRTS.2018.1
Deterministic Memory Abstraction and Supporting Multicore System Architecture

Authors: Farzad Farshchi, Prathap Kumar Valsan, Renato Mancuso, and Heechul Yun

Published in: LIPIcs, Volume 106, 30th Euromicro Conference on Real-Time Systems (ECRTS 2018)

Abstract
Poor time predictability of multicore processors has been a long-standing challenge in the real-time systems community. In this paper, we make a case that a fundamental problem that prevents efficient and predictable real-time computing on multicore is the lack of a proper memory abstraction to express memory criticality, which cuts across various layers of the system: the application, OS, and hardware. We, therefore, propose a new holistic resource management approach driven by a new memory abstraction, which we call Deterministic Memory. The key characteristic of deterministic memory is that the platform-the OS and hardware-guarantees small and tightly bounded worst-case memory access timing. In contrast, we call the conventional memory abstraction as best-effort memory in which only highly pessimistic worst-case bounds can be achieved. We propose to utilize both abstractions to achieve high time predictability but without significantly sacrificing performance. We present deterministic memory-aware OS and architecture designs, including OS-level page allocator, hardware-level cache, and DRAM controller designs. We implement the proposed OS and architecture extensions on Linux and gem5 simulator. Our evaluation results, using a set of synthetic and real-world benchmarks, demonstrate the feasibility and effectiveness of our approach.
Cite as

Farzad Farshchi, Prathap Kumar Valsan, Renato Mancuso, and Heechul Yun. Deterministic Memory Abstraction and Supporting Multicore System Architecture. In 30th Euromicro Conference on Real-Time Systems (ECRTS 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 106, pp. 1:1-1:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{farshchi_et_al:LIPIcs.ECRTS.2018.1,
  author =	{Farshchi, Farzad and Valsan, Prathap Kumar and Mancuso, Renato and Yun, Heechul},
  title =	{{Deterministic Memory Abstraction and Supporting Multicore System Architecture}},
  booktitle =	{30th Euromicro Conference on Real-Time Systems (ECRTS 2018)},
  pages =	{1:1--1:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-075-0},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{106},
  editor =	{Altmeyer, Sebastian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2018.1},
  URN =		{urn:nbn:de:0030-drops-90010},
  doi =		{10.4230/LIPIcs.ECRTS.2018.1},
  annote =	{Keywords: multicore processors, real-time, shared cache, DRAM controller, Linux}
}
Document
DOI: 10.4230/LIPIcs.ECRTS.2018.19
Protecting Real-Time GPU Kernels on Integrated CPU-GPU SoC Platforms

Authors: Waqar Ali and Heechul Yun

Published in: LIPIcs, Volume 106, 30th Euromicro Conference on Real-Time Systems (ECRTS 2018)

Abstract
Integrated CPU-GPU architecture provides excellent acceleration capabilities for data parallel applications on embedded platforms while meeting the size, weight and power (SWaP) requirements. However, sharing of main memory between CPU applications and GPU kernels can severely affect the execution of GPU kernels and diminish the performance gain provided by GPU. For example, in the NVIDIA Jetson TX2 platform, an integrated CPU-GPU architecture, we observed that, in the worst case, the GPU kernels can suffer as much as 3X slowdown in the presence of co-running memory intensive CPU applications. In this paper, we propose a software mechanism, which we call BWLOCK++, to protect the performance of GPU kernels from co-scheduled memory intensive CPU applications.
Cite as

Waqar Ali and Heechul Yun. Protecting Real-Time GPU Kernels on Integrated CPU-GPU SoC Platforms. In 30th Euromicro Conference on Real-Time Systems (ECRTS 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 106, pp. 19:1-19:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{ali_et_al:LIPIcs.ECRTS.2018.19,
  author =	{Ali, Waqar and Yun, Heechul},
  title =	{{Protecting Real-Time GPU Kernels on Integrated CPU-GPU SoC Platforms}},
  booktitle =	{30th Euromicro Conference on Real-Time Systems (ECRTS 2018)},
  pages =	{19:1--19:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-075-0},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{106},
  editor =	{Altmeyer, Sebastian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2018.19},
  URN =		{urn:nbn:de:0030-drops-89833},
  doi =		{10.4230/LIPIcs.ECRTS.2018.19},
  annote =	{Keywords: GPU, memory bandwidth, resource contention, CPU throttling, fair scheduler}
}
Document
DOI: 10.4230/DARTS.4.2.3
Protecting Real-Time GPU Kernels on Integrated CPU-GPU SoC Platforms (Artifact)

Authors: Waqar Ali and Heechul Yun

Published in: DARTS, Volume 4, Issue 2, Special Issue of the 30th Euromicro Conference on Real-Time Systems (ECRTS 2018)

Abstract
This artifact is based on BWLOCK++, a software framework to protect the performance of GPU kernels from co-scheduled memory intensive CPU applications in platforms containing integrated GPUs. The artifact is designed to support the claims of the companion paper and contains instructions on how to build and execute BWLOCK++ on a target hardware platform.
Cite as

Waqar Ali and Heechul Yun. Protecting Real-Time GPU Kernels on Integrated CPU-GPU SoC Platforms (Artifact). In Special Issue of the 30th Euromicro Conference on Real-Time Systems (ECRTS 2018). Dagstuhl Artifacts Series (DARTS), Volume 4, Issue 2, pp. 3:1-3:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@Article{ali_et_al:DARTS.4.2.3,
  author =	{Ali, Waqar and Yun, Heechul},
  title =	{{Protecting Real-Time GPU Kernels on Integrated CPU-GPU SoC Platforms (Artifact)}},
  pages =	{3:1--3:2},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2018},
  volume =	{4},
  number =	{2},
  editor =	{Ali, Waqar and Yun, Heechul},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.4.2.3},
  URN =		{urn:nbn:de:0030-drops-89719},
  doi =		{10.4230/DARTS.4.2.3},
  annote =	{Keywords: GPU, memory bandwidth, resource contention, CPU throttling, fair scheduler}
}
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