Lecture Notes in Computer Science - Embedded Computer Systems: Architectures, Modeling, and Simulation
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Published By Springer International Publishing

9783030275617, 9783030275624

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A Lean, Low Power, Low Latency DRAM Memory Controller for Transprecision Computing

Lecture Notes in Computer Science - Embedded Computer Systems: Architectures, Modeling, and Simulation ◽

10.1007/978-3-030-27562-4_31 ◽

2019 ◽

pp. 429-441 ◽

Cited By ~ 2

Author(s):

Chirag Sudarshan ◽

Jan Lappas ◽

Christian Weis ◽

Deepak M. Mathew ◽

Matthias Jung ◽

...

Keyword(s):

Low Power ◽

Low Latency ◽

Memory Controller

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GEMBench: A Platform for Collaborative Development of GPU Accelerated Embedded Markov Decision Systems

Lecture Notes in Computer Science - Embedded Computer Systems: Architectures, Modeling, and Simulation ◽

10.1007/978-3-030-27562-4_21 ◽

2019 ◽

pp. 294-308

Author(s):

Adrian E. Sapio ◽

Rocky L. Tatiefo ◽

Shuvra S. Bhattacharyya ◽

Marilyn Wolf

Keyword(s):

Collaborative Development ◽

Decision Systems ◽

Markov Decision

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Experimental Evaluation of Probabilistic Execution-Time Modeling and Analysis Methods for SDF Applications on MPSoCs

Lecture Notes in Computer Science - Embedded Computer Systems: Architectures, Modeling, and Simulation ◽

10.1007/978-3-030-27562-4_17 ◽

2019 ◽

pp. 241-254

Author(s):

Ralf Stemmer ◽

Hai-Dang Vu ◽

Kim Grüttner ◽

Sebastien Le Nours ◽

Wolfgang Nebel ◽

...

Keyword(s):

Execution Time ◽

Experimental Evaluation ◽

Modeling And Analysis ◽

Analysis Methods ◽

Time Modeling

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Design and Optimization of an ARM Cortex-M Based SoC for TCP/IP Communication in High Temperature Applications

Lecture Notes in Computer Science - Embedded Computer Systems: Architectures, Modeling, and Simulation ◽

10.1007/978-3-030-27562-4_12 ◽

2019 ◽

pp. 169-183 ◽

Cited By ~ 1

Author(s):

T. Stuckenberg ◽

M. Gottschlich ◽

S. Nolting ◽

H. Blume

Keyword(s):

High Temperature ◽

Design And Optimization ◽

Temperature Applications ◽

Ip Communication

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Transport Triggered Array Processor for Vision Applications

Lecture Notes in Computer Science - Embedded Computer Systems: Architectures, Modeling, and Simulation ◽

10.1007/978-3-030-27562-4_26 ◽

2019 ◽

pp. 361-372

Author(s):

Mehdi Safarpour ◽

Ilkka Hautala ◽

Miguel Bordallo López ◽

Olli Silvén

Keyword(s):

Array Processor

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Predictive Resource Management for Next-Generation High-Performance Computing Heterogeneous Platforms

Lecture Notes in Computer Science - Embedded Computer Systems: Architectures, Modeling, and Simulation ◽

10.1007/978-3-030-27562-4_34 ◽

2019 ◽

pp. 470-483 ◽

Cited By ~ 2

Author(s):

Giuseppe Massari ◽

Anna Pupykina ◽

Giovanni Agosta ◽

William Fornaciari

Keyword(s):

Resource Management ◽

High Performance Computing ◽

High Performance ◽

Next Generation ◽

Heterogeneous Platforms ◽

Performance Computing

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Modeling Nested for Loops with Explicit Parallelism in Synchronous DataFlow Graphs

Lecture Notes in Computer Science - Embedded Computer Systems: Architectures, Modeling, and Simulation ◽

10.1007/978-3-030-27562-4_19 ◽

2019 ◽

pp. 269-280

Author(s):

Alexandre Honorat ◽

Karol Desnos ◽

Maxime Pelcat ◽

Jean-François Nezan

Keyword(s):

Dataflow Graphs ◽

Synchronous Dataflow ◽

Synchronous Dataflow Graphs

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Hardware/Software Self-adaptation in CPS: The CERBERO Project Approach

Lecture Notes in Computer Science - Embedded Computer Systems: Architectures, Modeling, and Simulation ◽

10.1007/978-3-030-27562-4_30 ◽

2019 ◽

pp. 416-428 ◽

Cited By ~ 2

Author(s):

Francesca Palumbo ◽

Tiziana Fanni ◽

Carlo Sau ◽

Alfonso Rodríguez ◽

Daniel Madroñal ◽

...

Keyword(s):

Project Approach ◽

Self Adaptation

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Efficient Dynamic Device Placement for Deep Neural Network Training on Heterogeneous Systems

Lecture Notes in Computer Science - Embedded Computer Systems: Architectures, Modeling, and Simulation ◽

10.1007/978-3-030-27562-4_4 ◽

2019 ◽

pp. 51-64

Author(s):

Zi Xuan Huang ◽

Shen Yu Fu ◽

Wei Chung Hsu

Keyword(s):

Neural Network ◽

Deep Neural Network ◽

Heterogeneous Systems ◽

Neural Network Training ◽

Network Training ◽

Device Placement

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Automatic Memory-Efficient Scheduling of CNNs

Lecture Notes in Computer Science - Embedded Computer Systems: Architectures, Modeling, and Simulation ◽

10.1007/978-3-030-27562-4_28 ◽

2019 ◽

pp. 387-400

Author(s):

Luc Waeijen ◽

Savvas Sioutas ◽

Yifan He ◽

Maurice Peemen ◽

Henk Corporaal

Keyword(s):

Automatic Memory ◽

Memory Efficient

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Lecture Notes in Computer Science - Embedded Computer Systems: Architectures, Modeling, and SimulationLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

A Lean, Low Power, Low Latency DRAM Memory Controller for Transprecision Computing

GEMBench: A Platform for Collaborative Development of GPU Accelerated Embedded Markov Decision Systems

Experimental Evaluation of Probabilistic Execution-Time Modeling and Analysis Methods for SDF Applications on MPSoCs

Design and Optimization of an ARM Cortex-M Based SoC for TCP/IP Communication in High Temperature Applications

Transport Triggered Array Processor for Vision Applications

Predictive Resource Management for Next-Generation High-Performance Computing Heterogeneous Platforms

Modeling Nested for Loops with Explicit Parallelism in Synchronous DataFlow Graphs

Hardware/Software Self-adaptation in CPS: The CERBERO Project Approach

Efficient Dynamic Device Placement for Deep Neural Network Training on Heterogeneous Systems

Automatic Memory-Efficient Scheduling of CNNs

Lecture Notes in Computer Science - Embedded Computer Systems: Architectures, Modeling, and Simulation
Latest Publications