Abstract

In this report, we discuss the use of contemporary ray-tracing techniques to accelerate 3D mesh-based Monte Carlo photon transport simulations. Single Instruction Multiple Data (SIMD) based computation and branch-less design are exploited to accelerate ray-tetrahedron intersection tests and yield a 2-fold speed-up for ray-tracing calculations on a multi-core CPU. As part of this work, we have also studied SIMD-accelerated random number generators and math functions. The combination of these techniques achieved an overall improvement of 22% in simulation speed as compared to using a non-SIMD implementation. We applied this new method to analyze a complex numerical phantom and both the phantom data and the improved code are available as open-source software at http://mcx.sourceforge.net/mmc/.

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  1. D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Proc. Mag.18, 57–75 (2001).
    [CrossRef]
  2. A. P. Gibson, J. C. Hebden, and S. R. Arridge, “Recent advances in diffuse optical imaging,” Phys. Med. Biol.50, R1–R43 (2005).
    [CrossRef] [PubMed]
  3. L. H. Wang, S. L. Jacques, and L. Q. Zheng, “MCML - Monte Carlo modeling of light transport in multilayered tissues,” Comput. Meth. Prog. Bio.47, 131–146 (1995).
    [CrossRef]
  4. D. A. Boas, J. Culver, J. Stott, and A. Dunn, “Three dimensional Monte Carlo code for photon migration through complex heterogeneous media including the adult human head,” Opt. Express10, 159–170 (2002).
    [PubMed]
  5. Q. Fang and D. A. Boas, “Monte Carlo simulation of photon migration in 3D turbid media accelerated by graphics processing,” Opt. Express17, 20178–20190 (2009).
    [CrossRef] [PubMed]
  6. H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the monte carlo method,” Academ. Radiol.11, 1029–1038 (2004).
    [CrossRef]
  7. E. Margallo-Balbäs and P. J. French, “Shape based Monte Carlo code for light transport in complex heterogeneous Tissues,” Opt. Express15, 14086–14098 (2007).
    [CrossRef] [PubMed]
  8. N. Ren, J. Liang, X. Qu, J. Li, B. Lu, and J. Tian, “GPU-based Monte Carlo simulation for light propagation in complex heterogeneous tissues,” Opt. Express18, 6811–6823 (2010).
    [CrossRef] [PubMed]
  9. C. Wächter, “Quasi-Monte Carlo light transport simulation by efficient ray tracing,” Ph.D. dissertation (Ulm University, Ulm, Germany, 2007).
  10. I. Wald, “Realtime ray tracing and interactive global illumination,” Ph.D. dissertation (Saarland Univ., Saarbrücken, Germany, 2004).
  11. H. Shen and G. Wang, “A tetrahedron-based inhomogeneous Monte Carlo optical simulator,” Phys. Med. Biol.55, 947–962 (2010).
    [CrossRef] [PubMed]
  12. Q. Fang, “Mesh-based Monte Carlo method using fast ray-tracing in Plücker coordinates,” Biomed. Opt. Express1, 165–175 (2010).
    [CrossRef] [PubMed]
  13. Q. Fang, “Comment on ‘A study on tetrahedron-based inhomogeneous Monte-Carlo optical simulation’,” Biomed. Opt. Express2, 1258–1264 (2011).
    [CrossRef] [PubMed]
  14. CGAL Editorial Board, CGAL User and Reference Manual, 3rd ed. (2009).
  15. Q. Fang and D. A. Boas, “Tetrahedral mesh generation from volumetric binary and grayscale images,” in IEEE International Symposium on Biomedical Imaging: from Nano to Macro, 2009. ISBI ’09 (IEEE, 2009), pp. 1142–1145.
    [CrossRef]
  16. M. Shevtsov, A. Soupikov, and A. Kapustin, “Ray-triangle intersection algorithm for modern CPU architectures,” in Proceedings of GraphiCon 2007 (2007), Vol. 11, pp. 33–39.
  17. J. Havel and A. Herout, “Yet faster ray-triangle intersection (using SSE4),” IEEE Trans. Visualiz. Comput. Graphics16, 434–438 (2010).
    [CrossRef]
  18. D. Badouel, Graphics Gems (Academic, 1990).
  19. M. Saito and M. Matsumoto, Monte Carlo and Quasi-Monte Carlo Methods 2006 (Springer, 2008).
  20. J. Pommier, “Simple SSE and SSE2 optimized sin, cos, log and exp” (2007), http://gruntthepeon.free.fr/ssemath/ .
  21. B. Dogdas, D. Stout, A. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys Med Biol.52, 577–87 (2007).
    [CrossRef] [PubMed]
  22. W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electronics26, 2166–2185 (1990).
    [CrossRef]
  23. S. Powell and T. S. Leung, “Highly parallel Monte-Carlo simulations of the acousto-optic effect in heterogeneous turbid media,” J. Biomed. Opt.17, 045002 (2012).
    [CrossRef] [PubMed]

2012 (1)

S. Powell and T. S. Leung, “Highly parallel Monte-Carlo simulations of the acousto-optic effect in heterogeneous turbid media,” J. Biomed. Opt.17, 045002 (2012).
[CrossRef] [PubMed]

2011 (1)

Q. Fang, “Comment on ‘A study on tetrahedron-based inhomogeneous Monte-Carlo optical simulation’,” Biomed. Opt. Express2, 1258–1264 (2011).
[CrossRef] [PubMed]

2010 (4)

J. Havel and A. Herout, “Yet faster ray-triangle intersection (using SSE4),” IEEE Trans. Visualiz. Comput. Graphics16, 434–438 (2010).
[CrossRef]

N. Ren, J. Liang, X. Qu, J. Li, B. Lu, and J. Tian, “GPU-based Monte Carlo simulation for light propagation in complex heterogeneous tissues,” Opt. Express18, 6811–6823 (2010).
[CrossRef] [PubMed]

H. Shen and G. Wang, “A tetrahedron-based inhomogeneous Monte Carlo optical simulator,” Phys. Med. Biol.55, 947–962 (2010).
[CrossRef] [PubMed]

Q. Fang, “Mesh-based Monte Carlo method using fast ray-tracing in Plücker coordinates,” Biomed. Opt. Express1, 165–175 (2010).
[CrossRef] [PubMed]

2009 (1)

2007 (3)

B. Dogdas, D. Stout, A. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys Med Biol.52, 577–87 (2007).
[CrossRef] [PubMed]

M. Shevtsov, A. Soupikov, and A. Kapustin, “Ray-triangle intersection algorithm for modern CPU architectures,” in Proceedings of GraphiCon 2007 (2007), Vol. 11, pp. 33–39.

E. Margallo-Balbäs and P. J. French, “Shape based Monte Carlo code for light transport in complex heterogeneous Tissues,” Opt. Express15, 14086–14098 (2007).
[CrossRef] [PubMed]

2005 (1)

A. P. Gibson, J. C. Hebden, and S. R. Arridge, “Recent advances in diffuse optical imaging,” Phys. Med. Biol.50, R1–R43 (2005).
[CrossRef] [PubMed]

2004 (1)

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the monte carlo method,” Academ. Radiol.11, 1029–1038 (2004).
[CrossRef]

2002 (1)

2001 (1)

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Proc. Mag.18, 57–75 (2001).
[CrossRef]

1995 (1)

L. H. Wang, S. L. Jacques, and L. Q. Zheng, “MCML - Monte Carlo modeling of light transport in multilayered tissues,” Comput. Meth. Prog. Bio.47, 131–146 (1995).
[CrossRef]

1990 (1)

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electronics26, 2166–2185 (1990).
[CrossRef]

Arridge, S. R.

A. P. Gibson, J. C. Hebden, and S. R. Arridge, “Recent advances in diffuse optical imaging,” Phys. Med. Biol.50, R1–R43 (2005).
[CrossRef] [PubMed]

Badouel, D.

D. Badouel, Graphics Gems (Academic, 1990).

Boas, D. A.

Q. Fang and D. A. Boas, “Monte Carlo simulation of photon migration in 3D turbid media accelerated by graphics processing,” Opt. Express17, 20178–20190 (2009).
[CrossRef] [PubMed]

D. A. Boas, J. Culver, J. Stott, and A. Dunn, “Three dimensional Monte Carlo code for photon migration through complex heterogeneous media including the adult human head,” Opt. Express10, 159–170 (2002).
[PubMed]

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Proc. Mag.18, 57–75 (2001).
[CrossRef]

Q. Fang and D. A. Boas, “Tetrahedral mesh generation from volumetric binary and grayscale images,” in IEEE International Symposium on Biomedical Imaging: from Nano to Macro, 2009. ISBI ’09 (IEEE, 2009), pp. 1142–1145.
[CrossRef]

Brooks, D. H.

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Proc. Mag.18, 57–75 (2001).
[CrossRef]

Chatziioannou, A.

B. Dogdas, D. Stout, A. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys Med Biol.52, 577–87 (2007).
[CrossRef] [PubMed]

Cheong, W. F.

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electronics26, 2166–2185 (1990).
[CrossRef]

Cong, W.

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the monte carlo method,” Academ. Radiol.11, 1029–1038 (2004).
[CrossRef]

Culver, J.

DiMarzio, C. A.

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Proc. Mag.18, 57–75 (2001).
[CrossRef]

Dogdas, B.

B. Dogdas, D. Stout, A. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys Med Biol.52, 577–87 (2007).
[CrossRef] [PubMed]

Dunn, A.

Fang, Q.

Q. Fang, “Comment on ‘A study on tetrahedron-based inhomogeneous Monte-Carlo optical simulation’,” Biomed. Opt. Express2, 1258–1264 (2011).
[CrossRef] [PubMed]

Q. Fang, “Mesh-based Monte Carlo method using fast ray-tracing in Plücker coordinates,” Biomed. Opt. Express1, 165–175 (2010).
[CrossRef] [PubMed]

Q. Fang and D. A. Boas, “Monte Carlo simulation of photon migration in 3D turbid media accelerated by graphics processing,” Opt. Express17, 20178–20190 (2009).
[CrossRef] [PubMed]

Q. Fang and D. A. Boas, “Tetrahedral mesh generation from volumetric binary and grayscale images,” in IEEE International Symposium on Biomedical Imaging: from Nano to Macro, 2009. ISBI ’09 (IEEE, 2009), pp. 1142–1145.
[CrossRef]

French, P. J.

Gaudette, R. J.

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Proc. Mag.18, 57–75 (2001).
[CrossRef]

Gibson, A. P.

A. P. Gibson, J. C. Hebden, and S. R. Arridge, “Recent advances in diffuse optical imaging,” Phys. Med. Biol.50, R1–R43 (2005).
[CrossRef] [PubMed]

Havel, J.

J. Havel and A. Herout, “Yet faster ray-triangle intersection (using SSE4),” IEEE Trans. Visualiz. Comput. Graphics16, 434–438 (2010).
[CrossRef]

Hebden, J. C.

A. P. Gibson, J. C. Hebden, and S. R. Arridge, “Recent advances in diffuse optical imaging,” Phys. Med. Biol.50, R1–R43 (2005).
[CrossRef] [PubMed]

Herout, A.

J. Havel and A. Herout, “Yet faster ray-triangle intersection (using SSE4),” IEEE Trans. Visualiz. Comput. Graphics16, 434–438 (2010).
[CrossRef]

Hoffman, E. A.

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the monte carlo method,” Academ. Radiol.11, 1029–1038 (2004).
[CrossRef]

Jacques, S. L.

L. H. Wang, S. L. Jacques, and L. Q. Zheng, “MCML - Monte Carlo modeling of light transport in multilayered tissues,” Comput. Meth. Prog. Bio.47, 131–146 (1995).
[CrossRef]

Kapustin, A.

M. Shevtsov, A. Soupikov, and A. Kapustin, “Ray-triangle intersection algorithm for modern CPU architectures,” in Proceedings of GraphiCon 2007 (2007), Vol. 11, pp. 33–39.

Kilmer, M.

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Proc. Mag.18, 57–75 (2001).
[CrossRef]

Leahy, R. M.

B. Dogdas, D. Stout, A. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys Med Biol.52, 577–87 (2007).
[CrossRef] [PubMed]

Leung, T. S.

S. Powell and T. S. Leung, “Highly parallel Monte-Carlo simulations of the acousto-optic effect in heterogeneous turbid media,” J. Biomed. Opt.17, 045002 (2012).
[CrossRef] [PubMed]

Li, H.

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the monte carlo method,” Academ. Radiol.11, 1029–1038 (2004).
[CrossRef]

Li, J.

Liang, J.

Lu, B.

Margallo-Balbäs, E.

Matsumoto, M.

M. Saito and M. Matsumoto, Monte Carlo and Quasi-Monte Carlo Methods 2006 (Springer, 2008).

Miller, E. L.

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Proc. Mag.18, 57–75 (2001).
[CrossRef]

Powell, S.

S. Powell and T. S. Leung, “Highly parallel Monte-Carlo simulations of the acousto-optic effect in heterogeneous turbid media,” J. Biomed. Opt.17, 045002 (2012).
[CrossRef] [PubMed]

Prahl, S. A.

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electronics26, 2166–2185 (1990).
[CrossRef]

Qu, X.

Ren, N.

Saito, M.

M. Saito and M. Matsumoto, Monte Carlo and Quasi-Monte Carlo Methods 2006 (Springer, 2008).

Shen, H.

H. Shen and G. Wang, “A tetrahedron-based inhomogeneous Monte Carlo optical simulator,” Phys. Med. Biol.55, 947–962 (2010).
[CrossRef] [PubMed]

Shevtsov, M.

M. Shevtsov, A. Soupikov, and A. Kapustin, “Ray-triangle intersection algorithm for modern CPU architectures,” in Proceedings of GraphiCon 2007 (2007), Vol. 11, pp. 33–39.

Soupikov, A.

M. Shevtsov, A. Soupikov, and A. Kapustin, “Ray-triangle intersection algorithm for modern CPU architectures,” in Proceedings of GraphiCon 2007 (2007), Vol. 11, pp. 33–39.

Stott, J.

Stout, D.

B. Dogdas, D. Stout, A. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys Med Biol.52, 577–87 (2007).
[CrossRef] [PubMed]

Tian, J.

N. Ren, J. Liang, X. Qu, J. Li, B. Lu, and J. Tian, “GPU-based Monte Carlo simulation for light propagation in complex heterogeneous tissues,” Opt. Express18, 6811–6823 (2010).
[CrossRef] [PubMed]

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the monte carlo method,” Academ. Radiol.11, 1029–1038 (2004).
[CrossRef]

Wächter, C.

C. Wächter, “Quasi-Monte Carlo light transport simulation by efficient ray tracing,” Ph.D. dissertation (Ulm University, Ulm, Germany, 2007).

Wald, I.

I. Wald, “Realtime ray tracing and interactive global illumination,” Ph.D. dissertation (Saarland Univ., Saarbrücken, Germany, 2004).

Wang, G.

H. Shen and G. Wang, “A tetrahedron-based inhomogeneous Monte Carlo optical simulator,” Phys. Med. Biol.55, 947–962 (2010).
[CrossRef] [PubMed]

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the monte carlo method,” Academ. Radiol.11, 1029–1038 (2004).
[CrossRef]

Wang, L. H.

L. H. Wang, S. L. Jacques, and L. Q. Zheng, “MCML - Monte Carlo modeling of light transport in multilayered tissues,” Comput. Meth. Prog. Bio.47, 131–146 (1995).
[CrossRef]

Wang, L. V.

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the monte carlo method,” Academ. Radiol.11, 1029–1038 (2004).
[CrossRef]

Welch, A. J.

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electronics26, 2166–2185 (1990).
[CrossRef]

Zhang, Q.

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Proc. Mag.18, 57–75 (2001).
[CrossRef]

Zheng, L. Q.

L. H. Wang, S. L. Jacques, and L. Q. Zheng, “MCML - Monte Carlo modeling of light transport in multilayered tissues,” Comput. Meth. Prog. Bio.47, 131–146 (1995).
[CrossRef]

Zhu, F.

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the monte carlo method,” Academ. Radiol.11, 1029–1038 (2004).
[CrossRef]

Academ. Radiol. (1)

H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman, and G. Wang, “A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the monte carlo method,” Academ. Radiol.11, 1029–1038 (2004).
[CrossRef]

Biomed. Opt. Express (1)

Q. Fang, “Comment on ‘A study on tetrahedron-based inhomogeneous Monte-Carlo optical simulation’,” Biomed. Opt. Express2, 1258–1264 (2011).
[CrossRef] [PubMed]

Biomed. Opt. Express (1)

Comput. Meth. Prog. Bio. (1)

L. H. Wang, S. L. Jacques, and L. Q. Zheng, “MCML - Monte Carlo modeling of light transport in multilayered tissues,” Comput. Meth. Prog. Bio.47, 131–146 (1995).
[CrossRef]

IEEE J. Quantum Electronics (1)

W. F. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electronics26, 2166–2185 (1990).
[CrossRef]

IEEE Signal Proc. Mag. (1)

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Proc. Mag.18, 57–75 (2001).
[CrossRef]

IEEE Trans. Visualiz. Comput. Graphics (1)

J. Havel and A. Herout, “Yet faster ray-triangle intersection (using SSE4),” IEEE Trans. Visualiz. Comput. Graphics16, 434–438 (2010).
[CrossRef]

J. Biomed. Opt. (1)

S. Powell and T. S. Leung, “Highly parallel Monte-Carlo simulations of the acousto-optic effect in heterogeneous turbid media,” J. Biomed. Opt.17, 045002 (2012).
[CrossRef] [PubMed]

Opt. Express (4)

Phys Med Biol. (1)

B. Dogdas, D. Stout, A. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys Med Biol.52, 577–87 (2007).
[CrossRef] [PubMed]

Phys. Med. Biol. (2)

A. P. Gibson, J. C. Hebden, and S. R. Arridge, “Recent advances in diffuse optical imaging,” Phys. Med. Biol.50, R1–R43 (2005).
[CrossRef] [PubMed]

H. Shen and G. Wang, “A tetrahedron-based inhomogeneous Monte Carlo optical simulator,” Phys. Med. Biol.55, 947–962 (2010).
[CrossRef] [PubMed]

Proceedings of GraphiCon 2007 (1)

M. Shevtsov, A. Soupikov, and A. Kapustin, “Ray-triangle intersection algorithm for modern CPU architectures,” in Proceedings of GraphiCon 2007 (2007), Vol. 11, pp. 33–39.

Other (7)

CGAL Editorial Board, CGAL User and Reference Manual, 3rd ed. (2009).

Q. Fang and D. A. Boas, “Tetrahedral mesh generation from volumetric binary and grayscale images,” in IEEE International Symposium on Biomedical Imaging: from Nano to Macro, 2009. ISBI ’09 (IEEE, 2009), pp. 1142–1145.
[CrossRef]

D. Badouel, Graphics Gems (Academic, 1990).

M. Saito and M. Matsumoto, Monte Carlo and Quasi-Monte Carlo Methods 2006 (Springer, 2008).

J. Pommier, “Simple SSE and SSE2 optimized sin, cos, log and exp” (2007), http://gruntthepeon.free.fr/ssemath/ .

C. Wächter, “Quasi-Monte Carlo light transport simulation by efficient ray tracing,” Ph.D. dissertation (Ulm University, Ulm, Germany, 2007).

I. Wald, “Realtime ray tracing and interactive global illumination,” Ph.D. dissertation (Saarland Univ., Saarbrücken, Germany, 2004).

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Figures (2)

Fig. 1
Fig. 1

Subroutine-level profiling for mesh-based MC simulation (a) without SSE, (b) with Havel & Herout’s SSE-based algorithm, and (c) with additional SSE-enabled math library and RNG. The area and percentage in each block represent the run-time for each subroutine normalized by the total run-time of case (a). If a block is enclosed by another, its percentage contributes to that of the enclosing block. Profiling is performed within a single thread.

Fig. 2
Fig. 2

A tetrahedral mesh generated from the Digimouse atlas. Different colors represent different tissue types.

Tables (1)

Tables Icon

Table 1 Simulation run-times (in seconds) for various ray-tracers.

Metrics