Soft-core embedded FPGA based system on chip

Abstract Nowadays, there has been an intensive increase in embedded systems complexity. So that optimization and performance development become an interesting topic to study. In this proposal, the main problem to solve is to make the possibility to get more flexibility, to reduce cost and to improve...
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Autor*in:	Saidi, Hajer [verfasserIn] Turki, Mariem [verfasserIn] Marrakchi, Zied [verfasserIn] Abid, Mohamed [verfasserIn] Obeid, Abdulfattah [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	eFPGA Decoder Configuration Reconfigurable SoC

Anmerkung:	© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021

Übergeordnetes Werk:	Enthalten in: Analog integrated circuits and signal processing - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1991, 109(2021), 3 vom: 19. Mai, Seite 517-533
Übergeordnetes Werk:	volume:109 ; year:2021 ; number:3 ; day:19 ; month:05 ; pages:517-533

Links:	Volltext

DOI / URN:	10.1007/s10470-021-01872-5

Katalog-ID:	SPR045376549

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520			\|a Abstract Nowadays, there has been an intensive increase in embedded systems complexity. So that optimization and performance development become an interesting topic to study. In this proposal, the main problem to solve is to make the possibility to get more flexibility, to reduce cost and to improve performance. Considering this fact, we introduce in this paper a reconfigurable component integrated into Cortex M0 based System on Chip (SoC) which has the form of embedded FPGA. To the best of our knowledge, this is the first reconfigurable SoC composed of Tree-based embedded FPGA. Besides, we explored the different ways to reach the integration and the different steps. Then, we compared reconfigurable SoC with another developed SoC which contains many hardware accelerators which are a set of popular benchmarks in terms of performance and area. Finally, we take a popular error correction algorithm “RS-Encoder” as a test case. We made the profiling of this software application in order to compare the reconfigurable SoC with a classic SoC in terms of run-time. Preliminary results were presented and showed that the eFPGA integration introduces a chip area overhead but it proves interesting results in terms of run-time. Indeed, for 100 software instructions, the eFPGA is faster 4 times compared to a hardware accelerator and 412 times compared to the software implementation of the RS Encoder application.
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912			\|a GBV_ILN_150
912			\|a GBV_ILN_151
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912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_171
912			\|a GBV_ILN_187
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_250
912			\|a GBV_ILN_281
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
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912			\|a GBV_ILN_2038
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912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2056
912			\|a GBV_ILN_2057
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912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2093
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allfields	10.1007/s10470-021-01872-5 doi (DE-627)SPR045376549 (SPR)s10470-021-01872-5-e DE-627 ger DE-627 rakwb eng 004 ASE 53.55 bkl 53.73 bkl Saidi, Hajer verfasserin aut Soft-core embedded FPGA based system on chip 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 Abstract Nowadays, there has been an intensive increase in embedded systems complexity. So that optimization and performance development become an interesting topic to study. In this proposal, the main problem to solve is to make the possibility to get more flexibility, to reduce cost and to improve performance. Considering this fact, we introduce in this paper a reconfigurable component integrated into Cortex M0 based System on Chip (SoC) which has the form of embedded FPGA. To the best of our knowledge, this is the first reconfigurable SoC composed of Tree-based embedded FPGA. Besides, we explored the different ways to reach the integration and the different steps. Then, we compared reconfigurable SoC with another developed SoC which contains many hardware accelerators which are a set of popular benchmarks in terms of performance and area. Finally, we take a popular error correction algorithm “RS-Encoder” as a test case. We made the profiling of this software application in order to compare the reconfigurable SoC with a classic SoC in terms of run-time. Preliminary results were presented and showed that the eFPGA integration introduces a chip area overhead but it proves interesting results in terms of run-time. Indeed, for 100 software instructions, the eFPGA is faster 4 times compared to a hardware accelerator and 412 times compared to the software implementation of the RS Encoder application. eFPGA (dpeaa)DE-He213 Decoder (dpeaa)DE-He213 Configuration (dpeaa)DE-He213 Reconfigurable (dpeaa)DE-He213 SoC (dpeaa)DE-He213 Turki, Mariem verfasserin aut Marrakchi, Zied verfasserin aut Abid, Mohamed verfasserin aut Obeid, Abdulfattah verfasserin aut Enthalten in Analog integrated circuits and signal processing Dordrecht [u.a.] : Springer Science + Business Media B.V, 1991 109(2021), 3 vom: 19. Mai, Seite 517-533 (DE-627)271348925 (DE-600)1479772-0 1573-1979 nnns volume:109 year:2021 number:3 day:19 month:05 pages:517-533 https://dx.doi.org/10.1007/s10470-021-01872-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 53.55 ASE 53.73 ASE AR 109 2021 3 19 05 517-533
spelling	10.1007/s10470-021-01872-5 doi (DE-627)SPR045376549 (SPR)s10470-021-01872-5-e DE-627 ger DE-627 rakwb eng 004 ASE 53.55 bkl 53.73 bkl Saidi, Hajer verfasserin aut Soft-core embedded FPGA based system on chip 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 Abstract Nowadays, there has been an intensive increase in embedded systems complexity. So that optimization and performance development become an interesting topic to study. In this proposal, the main problem to solve is to make the possibility to get more flexibility, to reduce cost and to improve performance. Considering this fact, we introduce in this paper a reconfigurable component integrated into Cortex M0 based System on Chip (SoC) which has the form of embedded FPGA. To the best of our knowledge, this is the first reconfigurable SoC composed of Tree-based embedded FPGA. Besides, we explored the different ways to reach the integration and the different steps. Then, we compared reconfigurable SoC with another developed SoC which contains many hardware accelerators which are a set of popular benchmarks in terms of performance and area. Finally, we take a popular error correction algorithm “RS-Encoder” as a test case. We made the profiling of this software application in order to compare the reconfigurable SoC with a classic SoC in terms of run-time. Preliminary results were presented and showed that the eFPGA integration introduces a chip area overhead but it proves interesting results in terms of run-time. Indeed, for 100 software instructions, the eFPGA is faster 4 times compared to a hardware accelerator and 412 times compared to the software implementation of the RS Encoder application. eFPGA (dpeaa)DE-He213 Decoder (dpeaa)DE-He213 Configuration (dpeaa)DE-He213 Reconfigurable (dpeaa)DE-He213 SoC (dpeaa)DE-He213 Turki, Mariem verfasserin aut Marrakchi, Zied verfasserin aut Abid, Mohamed verfasserin aut Obeid, Abdulfattah verfasserin aut Enthalten in Analog integrated circuits and signal processing Dordrecht [u.a.] : Springer Science + Business Media B.V, 1991 109(2021), 3 vom: 19. Mai, Seite 517-533 (DE-627)271348925 (DE-600)1479772-0 1573-1979 nnns volume:109 year:2021 number:3 day:19 month:05 pages:517-533 https://dx.doi.org/10.1007/s10470-021-01872-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 53.55 ASE 53.73 ASE AR 109 2021 3 19 05 517-533
allfields_unstemmed	10.1007/s10470-021-01872-5 doi (DE-627)SPR045376549 (SPR)s10470-021-01872-5-e DE-627 ger DE-627 rakwb eng 004 ASE 53.55 bkl 53.73 bkl Saidi, Hajer verfasserin aut Soft-core embedded FPGA based system on chip 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 Abstract Nowadays, there has been an intensive increase in embedded systems complexity. So that optimization and performance development become an interesting topic to study. In this proposal, the main problem to solve is to make the possibility to get more flexibility, to reduce cost and to improve performance. Considering this fact, we introduce in this paper a reconfigurable component integrated into Cortex M0 based System on Chip (SoC) which has the form of embedded FPGA. To the best of our knowledge, this is the first reconfigurable SoC composed of Tree-based embedded FPGA. Besides, we explored the different ways to reach the integration and the different steps. Then, we compared reconfigurable SoC with another developed SoC which contains many hardware accelerators which are a set of popular benchmarks in terms of performance and area. Finally, we take a popular error correction algorithm “RS-Encoder” as a test case. We made the profiling of this software application in order to compare the reconfigurable SoC with a classic SoC in terms of run-time. Preliminary results were presented and showed that the eFPGA integration introduces a chip area overhead but it proves interesting results in terms of run-time. Indeed, for 100 software instructions, the eFPGA is faster 4 times compared to a hardware accelerator and 412 times compared to the software implementation of the RS Encoder application. eFPGA (dpeaa)DE-He213 Decoder (dpeaa)DE-He213 Configuration (dpeaa)DE-He213 Reconfigurable (dpeaa)DE-He213 SoC (dpeaa)DE-He213 Turki, Mariem verfasserin aut Marrakchi, Zied verfasserin aut Abid, Mohamed verfasserin aut Obeid, Abdulfattah verfasserin aut Enthalten in Analog integrated circuits and signal processing Dordrecht [u.a.] : Springer Science + Business Media B.V, 1991 109(2021), 3 vom: 19. Mai, Seite 517-533 (DE-627)271348925 (DE-600)1479772-0 1573-1979 nnns volume:109 year:2021 number:3 day:19 month:05 pages:517-533 https://dx.doi.org/10.1007/s10470-021-01872-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 53.55 ASE 53.73 ASE AR 109 2021 3 19 05 517-533
allfieldsGer	10.1007/s10470-021-01872-5 doi (DE-627)SPR045376549 (SPR)s10470-021-01872-5-e DE-627 ger DE-627 rakwb eng 004 ASE 53.55 bkl 53.73 bkl Saidi, Hajer verfasserin aut Soft-core embedded FPGA based system on chip 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 Abstract Nowadays, there has been an intensive increase in embedded systems complexity. So that optimization and performance development become an interesting topic to study. In this proposal, the main problem to solve is to make the possibility to get more flexibility, to reduce cost and to improve performance. Considering this fact, we introduce in this paper a reconfigurable component integrated into Cortex M0 based System on Chip (SoC) which has the form of embedded FPGA. To the best of our knowledge, this is the first reconfigurable SoC composed of Tree-based embedded FPGA. Besides, we explored the different ways to reach the integration and the different steps. Then, we compared reconfigurable SoC with another developed SoC which contains many hardware accelerators which are a set of popular benchmarks in terms of performance and area. Finally, we take a popular error correction algorithm “RS-Encoder” as a test case. We made the profiling of this software application in order to compare the reconfigurable SoC with a classic SoC in terms of run-time. Preliminary results were presented and showed that the eFPGA integration introduces a chip area overhead but it proves interesting results in terms of run-time. Indeed, for 100 software instructions, the eFPGA is faster 4 times compared to a hardware accelerator and 412 times compared to the software implementation of the RS Encoder application. eFPGA (dpeaa)DE-He213 Decoder (dpeaa)DE-He213 Configuration (dpeaa)DE-He213 Reconfigurable (dpeaa)DE-He213 SoC (dpeaa)DE-He213 Turki, Mariem verfasserin aut Marrakchi, Zied verfasserin aut Abid, Mohamed verfasserin aut Obeid, Abdulfattah verfasserin aut Enthalten in Analog integrated circuits and signal processing Dordrecht [u.a.] : Springer Science + Business Media B.V, 1991 109(2021), 3 vom: 19. Mai, Seite 517-533 (DE-627)271348925 (DE-600)1479772-0 1573-1979 nnns volume:109 year:2021 number:3 day:19 month:05 pages:517-533 https://dx.doi.org/10.1007/s10470-021-01872-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 53.55 ASE 53.73 ASE AR 109 2021 3 19 05 517-533
allfieldsSound	10.1007/s10470-021-01872-5 doi (DE-627)SPR045376549 (SPR)s10470-021-01872-5-e DE-627 ger DE-627 rakwb eng 004 ASE 53.55 bkl 53.73 bkl Saidi, Hajer verfasserin aut Soft-core embedded FPGA based system on chip 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 Abstract Nowadays, there has been an intensive increase in embedded systems complexity. So that optimization and performance development become an interesting topic to study. In this proposal, the main problem to solve is to make the possibility to get more flexibility, to reduce cost and to improve performance. Considering this fact, we introduce in this paper a reconfigurable component integrated into Cortex M0 based System on Chip (SoC) which has the form of embedded FPGA. To the best of our knowledge, this is the first reconfigurable SoC composed of Tree-based embedded FPGA. Besides, we explored the different ways to reach the integration and the different steps. Then, we compared reconfigurable SoC with another developed SoC which contains many hardware accelerators which are a set of popular benchmarks in terms of performance and area. Finally, we take a popular error correction algorithm “RS-Encoder” as a test case. We made the profiling of this software application in order to compare the reconfigurable SoC with a classic SoC in terms of run-time. Preliminary results were presented and showed that the eFPGA integration introduces a chip area overhead but it proves interesting results in terms of run-time. Indeed, for 100 software instructions, the eFPGA is faster 4 times compared to a hardware accelerator and 412 times compared to the software implementation of the RS Encoder application. eFPGA (dpeaa)DE-He213 Decoder (dpeaa)DE-He213 Configuration (dpeaa)DE-He213 Reconfigurable (dpeaa)DE-He213 SoC (dpeaa)DE-He213 Turki, Mariem verfasserin aut Marrakchi, Zied verfasserin aut Abid, Mohamed verfasserin aut Obeid, Abdulfattah verfasserin aut Enthalten in Analog integrated circuits and signal processing Dordrecht [u.a.] : Springer Science + Business Media B.V, 1991 109(2021), 3 vom: 19. Mai, Seite 517-533 (DE-627)271348925 (DE-600)1479772-0 1573-1979 nnns volume:109 year:2021 number:3 day:19 month:05 pages:517-533 https://dx.doi.org/10.1007/s10470-021-01872-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 53.55 ASE 53.73 ASE AR 109 2021 3 19 05 517-533
language	English
source	Enthalten in Analog integrated circuits and signal processing 109(2021), 3 vom: 19. Mai, Seite 517-533 volume:109 year:2021 number:3 day:19 month:05 pages:517-533
sourceStr	Enthalten in Analog integrated circuits and signal processing 109(2021), 3 vom: 19. Mai, Seite 517-533 volume:109 year:2021 number:3 day:19 month:05 pages:517-533
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	eFPGA Decoder Configuration Reconfigurable SoC
dewey-raw	004
isfreeaccess_bool	false
container_title	Analog integrated circuits and signal processing
authorswithroles_txt_mv	Saidi, Hajer @@aut@@ Turki, Mariem @@aut@@ Marrakchi, Zied @@aut@@ Abid, Mohamed @@aut@@ Obeid, Abdulfattah @@aut@@
publishDateDaySort_date	2021-05-19T00:00:00Z
hierarchy_top_id	271348925
dewey-sort	14
id	SPR045376549
language_de	englisch
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author	Saidi, Hajer
spellingShingle	Saidi, Hajer ddc 004 bkl 53.55 bkl 53.73 misc eFPGA misc Decoder misc Configuration misc Reconfigurable misc SoC Soft-core embedded FPGA based system on chip
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topic_title	004 ASE 53.55 bkl 53.73 bkl Soft-core embedded FPGA based system on chip eFPGA (dpeaa)DE-He213 Decoder (dpeaa)DE-He213 Configuration (dpeaa)DE-He213 Reconfigurable (dpeaa)DE-He213 SoC (dpeaa)DE-He213
topic	ddc 004 bkl 53.55 bkl 53.73 misc eFPGA misc Decoder misc Configuration misc Reconfigurable misc SoC
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title	Soft-core embedded FPGA based system on chip
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title_full	Soft-core embedded FPGA based system on chip
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title_sort	soft-core embedded fpga based system on chip
title_auth	Soft-core embedded FPGA based system on chip
abstract	Abstract Nowadays, there has been an intensive increase in embedded systems complexity. So that optimization and performance development become an interesting topic to study. In this proposal, the main problem to solve is to make the possibility to get more flexibility, to reduce cost and to improve performance. Considering this fact, we introduce in this paper a reconfigurable component integrated into Cortex M0 based System on Chip (SoC) which has the form of embedded FPGA. To the best of our knowledge, this is the first reconfigurable SoC composed of Tree-based embedded FPGA. Besides, we explored the different ways to reach the integration and the different steps. Then, we compared reconfigurable SoC with another developed SoC which contains many hardware accelerators which are a set of popular benchmarks in terms of performance and area. Finally, we take a popular error correction algorithm “RS-Encoder” as a test case. We made the profiling of this software application in order to compare the reconfigurable SoC with a classic SoC in terms of run-time. Preliminary results were presented and showed that the eFPGA integration introduces a chip area overhead but it proves interesting results in terms of run-time. Indeed, for 100 software instructions, the eFPGA is faster 4 times compared to a hardware accelerator and 412 times compared to the software implementation of the RS Encoder application. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021
abstractGer	Abstract Nowadays, there has been an intensive increase in embedded systems complexity. So that optimization and performance development become an interesting topic to study. In this proposal, the main problem to solve is to make the possibility to get more flexibility, to reduce cost and to improve performance. Considering this fact, we introduce in this paper a reconfigurable component integrated into Cortex M0 based System on Chip (SoC) which has the form of embedded FPGA. To the best of our knowledge, this is the first reconfigurable SoC composed of Tree-based embedded FPGA. Besides, we explored the different ways to reach the integration and the different steps. Then, we compared reconfigurable SoC with another developed SoC which contains many hardware accelerators which are a set of popular benchmarks in terms of performance and area. Finally, we take a popular error correction algorithm “RS-Encoder” as a test case. We made the profiling of this software application in order to compare the reconfigurable SoC with a classic SoC in terms of run-time. Preliminary results were presented and showed that the eFPGA integration introduces a chip area overhead but it proves interesting results in terms of run-time. Indeed, for 100 software instructions, the eFPGA is faster 4 times compared to a hardware accelerator and 412 times compared to the software implementation of the RS Encoder application. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021
abstract_unstemmed	Abstract Nowadays, there has been an intensive increase in embedded systems complexity. So that optimization and performance development become an interesting topic to study. In this proposal, the main problem to solve is to make the possibility to get more flexibility, to reduce cost and to improve performance. Considering this fact, we introduce in this paper a reconfigurable component integrated into Cortex M0 based System on Chip (SoC) which has the form of embedded FPGA. To the best of our knowledge, this is the first reconfigurable SoC composed of Tree-based embedded FPGA. Besides, we explored the different ways to reach the integration and the different steps. Then, we compared reconfigurable SoC with another developed SoC which contains many hardware accelerators which are a set of popular benchmarks in terms of performance and area. Finally, we take a popular error correction algorithm “RS-Encoder” as a test case. We made the profiling of this software application in order to compare the reconfigurable SoC with a classic SoC in terms of run-time. Preliminary results were presented and showed that the eFPGA integration introduces a chip area overhead but it proves interesting results in terms of run-time. Indeed, for 100 software instructions, the eFPGA is faster 4 times compared to a hardware accelerator and 412 times compared to the software implementation of the RS Encoder application. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021
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title_short	Soft-core embedded FPGA based system on chip
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So that optimization and performance development become an interesting topic to study. In this proposal, the main problem to solve is to make the possibility to get more flexibility, to reduce cost and to improve performance. Considering this fact, we introduce in this paper a reconfigurable component integrated into Cortex M0 based System on Chip (SoC) which has the form of embedded FPGA. To the best of our knowledge, this is the first reconfigurable SoC composed of Tree-based embedded FPGA. Besides, we explored the different ways to reach the integration and the different steps. Then, we compared reconfigurable SoC with another developed SoC which contains many hardware accelerators which are a set of popular benchmarks in terms of performance and area. Finally, we take a popular error correction algorithm “RS-Encoder” as a test case. We made the profiling of this software application in order to compare the reconfigurable SoC with a classic SoC in terms of run-time. Preliminary results were presented and showed that the eFPGA integration introduces a chip area overhead but it proves interesting results in terms of run-time. 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