Fast electrostatic halftoning
Abstract Electrostatic halftoning is a high-quality method for stippling, dithering, and sampling, but it suffers from a high runtime. This made the technique difficult to use for most real-world applications. A recently proposed minimisation scheme based on the non-equispaced fast Fourier transform...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Gwosdek, Pascal [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2011 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag 2011 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of real-time image processing - Berlin : Springer, 2006, 9(2011), 2 vom: 24. Dez., Seite 379-392 |
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| Übergeordnetes Werk: |
volume:9 ; year:2011 ; number:2 ; day:24 ; month:12 ; pages:379-392 |
| Links: |
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| DOI / URN: |
10.1007/s11554-011-0236-3 |
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| Katalog-ID: |
SPR020735278 |
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| 520 | |a Abstract Electrostatic halftoning is a high-quality method for stippling, dithering, and sampling, but it suffers from a high runtime. This made the technique difficult to use for most real-world applications. A recently proposed minimisation scheme based on the non-equispaced fast Fourier transform (NFFT) lowers the complexity in the particle number M from %$\mathcal{O}(M^2)%$ to %$\mathcal{O}(M \log M).%$ However, the NFFT is hard to parallelise, and the runtime on modern CPUs lies still in the orders of an hour for about 50,000 particles, to a day for 1 million particles. Our contributions to remedy this problem are threefold: we design the first GPU-based NFFT algorithm without special structural assumptions on the positions of nodes, we introduce a novel nearest-neighbour identification scheme for continuous point distributions, and we optimise the whole algorithm for n-body problems such as electrostatic halftoning. For 1 million particles, this new algorithm runs 50 times faster than the most efficient technique on the CPU, and even yields a speedup of 7,000 over the original algorithm. | ||
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| 650 | 4 | |a Fast Summation Algorithm |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Sampling |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Halftoning |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Schmaltz, Christian |4 aut | |
| 700 | 1 | |a Weickert, Joachim |4 aut | |
| 700 | 1 | |a Teuber, Tanja |4 aut | |
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10.1007/s11554-011-0236-3 doi (DE-627)SPR020735278 (SPR)s11554-011-0236-3-e DE-627 ger DE-627 rakwb eng Gwosdek, Pascal verfasserin aut Fast electrostatic halftoning 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2011 Abstract Electrostatic halftoning is a high-quality method for stippling, dithering, and sampling, but it suffers from a high runtime. This made the technique difficult to use for most real-world applications. A recently proposed minimisation scheme based on the non-equispaced fast Fourier transform (NFFT) lowers the complexity in the particle number M from %$\mathcal{O}(M^2)%$ to %$\mathcal{O}(M \log M).%$ However, the NFFT is hard to parallelise, and the runtime on modern CPUs lies still in the orders of an hour for about 50,000 particles, to a day for 1 million particles. Our contributions to remedy this problem are threefold: we design the first GPU-based NFFT algorithm without special structural assumptions on the positions of nodes, we introduce a novel nearest-neighbour identification scheme for continuous point distributions, and we optimise the whole algorithm for n-body problems such as electrostatic halftoning. For 1 million particles, this new algorithm runs 50 times faster than the most efficient technique on the CPU, and even yields a speedup of 7,000 over the original algorithm. NFFT (dpeaa)DE-He213 GPU (dpeaa)DE-He213 Fast Summation Algorithm (dpeaa)DE-He213 Sampling (dpeaa)DE-He213 Halftoning (dpeaa)DE-He213 Schmaltz, Christian aut Weickert, Joachim aut Teuber, Tanja aut Enthalten in Journal of real-time image processing Berlin : Springer, 2006 9(2011), 2 vom: 24. Dez., Seite 379-392 (DE-627)52836118X (DE-600)2280192-3 1861-8219 nnns volume:9 year:2011 number:2 day:24 month:12 pages:379-392 https://dx.doi.org/10.1007/s11554-011-0236-3 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_65 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 9 2011 2 24 12 379-392 |
| spelling |
10.1007/s11554-011-0236-3 doi (DE-627)SPR020735278 (SPR)s11554-011-0236-3-e DE-627 ger DE-627 rakwb eng Gwosdek, Pascal verfasserin aut Fast electrostatic halftoning 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2011 Abstract Electrostatic halftoning is a high-quality method for stippling, dithering, and sampling, but it suffers from a high runtime. This made the technique difficult to use for most real-world applications. A recently proposed minimisation scheme based on the non-equispaced fast Fourier transform (NFFT) lowers the complexity in the particle number M from %$\mathcal{O}(M^2)%$ to %$\mathcal{O}(M \log M).%$ However, the NFFT is hard to parallelise, and the runtime on modern CPUs lies still in the orders of an hour for about 50,000 particles, to a day for 1 million particles. Our contributions to remedy this problem are threefold: we design the first GPU-based NFFT algorithm without special structural assumptions on the positions of nodes, we introduce a novel nearest-neighbour identification scheme for continuous point distributions, and we optimise the whole algorithm for n-body problems such as electrostatic halftoning. For 1 million particles, this new algorithm runs 50 times faster than the most efficient technique on the CPU, and even yields a speedup of 7,000 over the original algorithm. NFFT (dpeaa)DE-He213 GPU (dpeaa)DE-He213 Fast Summation Algorithm (dpeaa)DE-He213 Sampling (dpeaa)DE-He213 Halftoning (dpeaa)DE-He213 Schmaltz, Christian aut Weickert, Joachim aut Teuber, Tanja aut Enthalten in Journal of real-time image processing Berlin : Springer, 2006 9(2011), 2 vom: 24. Dez., Seite 379-392 (DE-627)52836118X (DE-600)2280192-3 1861-8219 nnns volume:9 year:2011 number:2 day:24 month:12 pages:379-392 https://dx.doi.org/10.1007/s11554-011-0236-3 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_65 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 9 2011 2 24 12 379-392 |
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10.1007/s11554-011-0236-3 doi (DE-627)SPR020735278 (SPR)s11554-011-0236-3-e DE-627 ger DE-627 rakwb eng Gwosdek, Pascal verfasserin aut Fast electrostatic halftoning 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2011 Abstract Electrostatic halftoning is a high-quality method for stippling, dithering, and sampling, but it suffers from a high runtime. This made the technique difficult to use for most real-world applications. A recently proposed minimisation scheme based on the non-equispaced fast Fourier transform (NFFT) lowers the complexity in the particle number M from %$\mathcal{O}(M^2)%$ to %$\mathcal{O}(M \log M).%$ However, the NFFT is hard to parallelise, and the runtime on modern CPUs lies still in the orders of an hour for about 50,000 particles, to a day for 1 million particles. Our contributions to remedy this problem are threefold: we design the first GPU-based NFFT algorithm without special structural assumptions on the positions of nodes, we introduce a novel nearest-neighbour identification scheme for continuous point distributions, and we optimise the whole algorithm for n-body problems such as electrostatic halftoning. For 1 million particles, this new algorithm runs 50 times faster than the most efficient technique on the CPU, and even yields a speedup of 7,000 over the original algorithm. NFFT (dpeaa)DE-He213 GPU (dpeaa)DE-He213 Fast Summation Algorithm (dpeaa)DE-He213 Sampling (dpeaa)DE-He213 Halftoning (dpeaa)DE-He213 Schmaltz, Christian aut Weickert, Joachim aut Teuber, Tanja aut Enthalten in Journal of real-time image processing Berlin : Springer, 2006 9(2011), 2 vom: 24. Dez., Seite 379-392 (DE-627)52836118X (DE-600)2280192-3 1861-8219 nnns volume:9 year:2011 number:2 day:24 month:12 pages:379-392 https://dx.doi.org/10.1007/s11554-011-0236-3 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_65 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 9 2011 2 24 12 379-392 |
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10.1007/s11554-011-0236-3 doi (DE-627)SPR020735278 (SPR)s11554-011-0236-3-e DE-627 ger DE-627 rakwb eng Gwosdek, Pascal verfasserin aut Fast electrostatic halftoning 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2011 Abstract Electrostatic halftoning is a high-quality method for stippling, dithering, and sampling, but it suffers from a high runtime. This made the technique difficult to use for most real-world applications. A recently proposed minimisation scheme based on the non-equispaced fast Fourier transform (NFFT) lowers the complexity in the particle number M from %$\mathcal{O}(M^2)%$ to %$\mathcal{O}(M \log M).%$ However, the NFFT is hard to parallelise, and the runtime on modern CPUs lies still in the orders of an hour for about 50,000 particles, to a day for 1 million particles. Our contributions to remedy this problem are threefold: we design the first GPU-based NFFT algorithm without special structural assumptions on the positions of nodes, we introduce a novel nearest-neighbour identification scheme for continuous point distributions, and we optimise the whole algorithm for n-body problems such as electrostatic halftoning. For 1 million particles, this new algorithm runs 50 times faster than the most efficient technique on the CPU, and even yields a speedup of 7,000 over the original algorithm. NFFT (dpeaa)DE-He213 GPU (dpeaa)DE-He213 Fast Summation Algorithm (dpeaa)DE-He213 Sampling (dpeaa)DE-He213 Halftoning (dpeaa)DE-He213 Schmaltz, Christian aut Weickert, Joachim aut Teuber, Tanja aut Enthalten in Journal of real-time image processing Berlin : Springer, 2006 9(2011), 2 vom: 24. Dez., Seite 379-392 (DE-627)52836118X (DE-600)2280192-3 1861-8219 nnns volume:9 year:2011 number:2 day:24 month:12 pages:379-392 https://dx.doi.org/10.1007/s11554-011-0236-3 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_65 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 9 2011 2 24 12 379-392 |
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10.1007/s11554-011-0236-3 doi (DE-627)SPR020735278 (SPR)s11554-011-0236-3-e DE-627 ger DE-627 rakwb eng Gwosdek, Pascal verfasserin aut Fast electrostatic halftoning 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2011 Abstract Electrostatic halftoning is a high-quality method for stippling, dithering, and sampling, but it suffers from a high runtime. This made the technique difficult to use for most real-world applications. A recently proposed minimisation scheme based on the non-equispaced fast Fourier transform (NFFT) lowers the complexity in the particle number M from %$\mathcal{O}(M^2)%$ to %$\mathcal{O}(M \log M).%$ However, the NFFT is hard to parallelise, and the runtime on modern CPUs lies still in the orders of an hour for about 50,000 particles, to a day for 1 million particles. Our contributions to remedy this problem are threefold: we design the first GPU-based NFFT algorithm without special structural assumptions on the positions of nodes, we introduce a novel nearest-neighbour identification scheme for continuous point distributions, and we optimise the whole algorithm for n-body problems such as electrostatic halftoning. For 1 million particles, this new algorithm runs 50 times faster than the most efficient technique on the CPU, and even yields a speedup of 7,000 over the original algorithm. NFFT (dpeaa)DE-He213 GPU (dpeaa)DE-He213 Fast Summation Algorithm (dpeaa)DE-He213 Sampling (dpeaa)DE-He213 Halftoning (dpeaa)DE-He213 Schmaltz, Christian aut Weickert, Joachim aut Teuber, Tanja aut Enthalten in Journal of real-time image processing Berlin : Springer, 2006 9(2011), 2 vom: 24. Dez., Seite 379-392 (DE-627)52836118X (DE-600)2280192-3 1861-8219 nnns volume:9 year:2011 number:2 day:24 month:12 pages:379-392 https://dx.doi.org/10.1007/s11554-011-0236-3 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_65 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 9 2011 2 24 12 379-392 |
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Gwosdek, Pascal @@aut@@ Schmaltz, Christian @@aut@@ Weickert, Joachim @@aut@@ Teuber, Tanja @@aut@@ |
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Gwosdek, Pascal |
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Fast electrostatic halftoning NFFT (dpeaa)DE-He213 GPU (dpeaa)DE-He213 Fast Summation Algorithm (dpeaa)DE-He213 Sampling (dpeaa)DE-He213 Halftoning (dpeaa)DE-He213 |
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fast electrostatic halftoning |
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Fast electrostatic halftoning |
| abstract |
Abstract Electrostatic halftoning is a high-quality method for stippling, dithering, and sampling, but it suffers from a high runtime. This made the technique difficult to use for most real-world applications. A recently proposed minimisation scheme based on the non-equispaced fast Fourier transform (NFFT) lowers the complexity in the particle number M from %$\mathcal{O}(M^2)%$ to %$\mathcal{O}(M \log M).%$ However, the NFFT is hard to parallelise, and the runtime on modern CPUs lies still in the orders of an hour for about 50,000 particles, to a day for 1 million particles. Our contributions to remedy this problem are threefold: we design the first GPU-based NFFT algorithm without special structural assumptions on the positions of nodes, we introduce a novel nearest-neighbour identification scheme for continuous point distributions, and we optimise the whole algorithm for n-body problems such as electrostatic halftoning. For 1 million particles, this new algorithm runs 50 times faster than the most efficient technique on the CPU, and even yields a speedup of 7,000 over the original algorithm. © Springer-Verlag 2011 |
| abstractGer |
Abstract Electrostatic halftoning is a high-quality method for stippling, dithering, and sampling, but it suffers from a high runtime. This made the technique difficult to use for most real-world applications. A recently proposed minimisation scheme based on the non-equispaced fast Fourier transform (NFFT) lowers the complexity in the particle number M from %$\mathcal{O}(M^2)%$ to %$\mathcal{O}(M \log M).%$ However, the NFFT is hard to parallelise, and the runtime on modern CPUs lies still in the orders of an hour for about 50,000 particles, to a day for 1 million particles. Our contributions to remedy this problem are threefold: we design the first GPU-based NFFT algorithm without special structural assumptions on the positions of nodes, we introduce a novel nearest-neighbour identification scheme for continuous point distributions, and we optimise the whole algorithm for n-body problems such as electrostatic halftoning. For 1 million particles, this new algorithm runs 50 times faster than the most efficient technique on the CPU, and even yields a speedup of 7,000 over the original algorithm. © Springer-Verlag 2011 |
| abstract_unstemmed |
Abstract Electrostatic halftoning is a high-quality method for stippling, dithering, and sampling, but it suffers from a high runtime. This made the technique difficult to use for most real-world applications. A recently proposed minimisation scheme based on the non-equispaced fast Fourier transform (NFFT) lowers the complexity in the particle number M from %$\mathcal{O}(M^2)%$ to %$\mathcal{O}(M \log M).%$ However, the NFFT is hard to parallelise, and the runtime on modern CPUs lies still in the orders of an hour for about 50,000 particles, to a day for 1 million particles. Our contributions to remedy this problem are threefold: we design the first GPU-based NFFT algorithm without special structural assumptions on the positions of nodes, we introduce a novel nearest-neighbour identification scheme for continuous point distributions, and we optimise the whole algorithm for n-body problems such as electrostatic halftoning. For 1 million particles, this new algorithm runs 50 times faster than the most efficient technique on the CPU, and even yields a speedup of 7,000 over the original algorithm. © Springer-Verlag 2011 |
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Fast electrostatic halftoning |
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https://dx.doi.org/10.1007/s11554-011-0236-3 |
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Schmaltz, Christian Weickert, Joachim Teuber, Tanja |
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2024-07-03T17:56:30.498Z |
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| score |
7.4022093 |