Reconfigurable Computing: Architectures, Tools and Applications

9th International Symposium, ARC 2013, Los Angeles, CA, USA, March 25-27, 2013, Proceedings

AvPhilip Brisk,José Gabriel de Figueiredo Coutinho

Häftad, Engelska, 2013

Del i serien Lecture Notes in Computer Science

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Beskrivning

This book constitutes the thoroughly refereed conference proceedings of the 9th International Symposium on Reconfigurable Computing: Architectures, Tools and Applications, ARC 2013, held in Los Angeles, CA, USA, in March 2013. The 28 revised papers presented, consisting of 20 full papers and 11 poster papers were carefully selected from 41 submissions. The topics covered are applications, arithmetic, design optimization for FPGAs, architectures, place and routing.

Produktinformation

Utgivningsdatum:2013-02-09
Mått:155 x 235 x 15 mm
Vikt:394 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:238
Upplaga:2013
Förlag:Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN:9783642368110

Utforska kategorier

Elektronik och kommunikationer inom Naturvetenskap och teknik
Systemvetenskap och AI inom Data och IT
Hårdvara inom Data och IT

Innehållsförteckning

Heterogeneous Reconfigurable System for Adaptive Particle Filters in Real-Time Applications.- Hardware Acceleration of Genetic Sequence Alignment.- An FPGA Acceleration for the Kd-tree Search in Photon Mapping.- SEU Resilience of DES, AES in SRAM-based FPGA.- An Architecture for IPv6 Lookup Using Parallel Index Generation Units.- Hardware Index to Set Partition Converter.- Teaching SoC Using Video Games to Improve Student Engagement.- Parameterized Design and Evaluation of Bandwidth Compressor for Floating-Point Data Streams in FPGA-based Custom Computing.- Hardware Acceleration of Matrix Multiplication Over Small Prime Finite Fields.- Flexible Design of a Modular Simultaneous Exponentiation Core for Embedded Platforms.- Architecture for Transparent Binary Acceleration of Loops with Memory Accesses.- Parametric Optimization of Reconfigurable Designs using Machine Learning.- Fast Template-based Heterogeneous MPSoC Synthesis on FPGA.- Hierarchical and Multiple Switching NoC with Floorplan based Adaptability.- Performance Analysis And Optimization of High Density Tree-Based 3D Multilevel FPGA.