ACEMD: HIGH-THROUGHPUT
MOLECULAR DYNAMICS WITH NVIDIA
KEPLER GPUS
info@acellera.com


www.acellera.com
-  M. Harvey, G. Giupponi and G. De Fabritiis, ACEMD: Accelerating biomolecular dynamics in the
microsecond time scale, J....
Paradigms of molecular dynamics
High performance!
•  A single or few simulations
run for very long
•  Reached simulations ...
Binding processes
Direct!

A+B	
  

Intermediate!

AB	
  

A+B	
  

www.acellera.com

AB*	
  

AB	
  
SH2-pYEII

•  T. Giorgino, I. Buch and G. De Fabritiis, J. Chem. Theory Comput.,8, 1171–
1175 (2012).
www.acellera.com
FAAH-AEA

• 

E. Dainese, G. De Fabritiis et al. submitted (2013).
www.acellera.com
IN-SILICO LIGAND BINDING
Trypsin-Benzamidine

I. Buch, T. Giorgino and G. De Fabritiis,Complete reconstruction of an enzym...
Free ligand binding simulations!


35,000
 atoms
500 trajectories
100
 ns/each
50
µs of data




Beta-Trypsin/Benzamidine ...
Calculating kinetics of binding
Assuming first order kinetics

www.acellera.com
Guilliain

Singhal N et al. J Chem Phys (20...
Characteristic transition modes

www.acellera.com
Trypsin-benzamidine from X-ray

a)  Poses of Benzamidine on Trypsin detected through high pressure x-ray crystallography
b...
FBDD ON FACTOR XA
With Noelia Ferruz Capapey (Universitat Pompeu Fabra)
Matt Harvey (ACELLERA), Jordi Mestres (IMIM)

www....
S1	
  
S4	
  

[1] Lee Fielding ,  Dan Fletcher ,  Samantha Rutherford ,  Jasmit
Kaurand,  Jordi Mestres. Exploring the ac...
Library of
compounds

34 compounds 
screened by STD-NMR

9 ligands
bound to factor Xa

4 ligands 
selected for further
stu...
Three derived by known inhibitors

www.acellera.com
Experimental competition
assays with TPAM
•  Binding sites positions
were hypothesized from
similarity to known
ligands:
•...
METHODS
•  34 ligands built, simulated by
MD and analyzed b means of
Markov State Models
•  Protein structure from human
F...
Kinetics and thermodynamics
Ligand

Kd (µM)

Residence Time (ns.)

∆G (kcal/mol)

kon(s-1·M)

koff (s-1)

29

126.9 ± 56.9...
www.acellera.com
LIGAND 27
Experimental results!
• 
• 

Computational results!

Weakly displaced by TPAM.
Hypothesized to bind at S4 pocket...
www.acellera.com
LIGAND 10
Experimental results!
• 
• 

Computational results!

Clearly displaced by TPAM.
Expected to bind at pocket S4 by...
LIGAND 29
Experimental results!
• 
• 

Computational results!

Clearly displaced by TPAM.
Hypothesized to bind at S1 pocke...
LIGAND 31
Experimental results!
• 
• 
• 

Computational results!

KD = 30µM
Failure to be displaced by TPAM.
Expected to b...
Ensemble view with TPAM

www.acellera.com
METHODS
From hardware to software
www.acellera.com
“Molecular simulation will mature within the next 5 years to
allow simulations at temporal scales of biological interest, ...
ACEMD - History
• 

Developed from CellMD (2006), 19 times a CPU 

• 

First CUDA GPUs released 2006

• 

ACEMD released 2...
ACEMD - Capabilities
ACEMD has all the features required for production simulations of
biomolecules:

• 
• 
• 
• 

Major f...
ACEMD - Resources
User manual
Extensions developer manual 
Protocols manuals
Support forum for everybody
support@acellera....
ACEMD - Performance
DHFR	
  

Exceptional single GPU performance
Parallel scaling up to 1.4x on 3 GPUs
(single host)

Tita...
ACEMD – Free basic download
•  Optimal if you do little use of MD
•  Have only single GPU machines in your lab
•  Fully fu...
ACEMD - Extensions
•  ACEMD can be extended by the user
• 

TCL – coded directly in input file

• 

Plugins – separate bina...
ACEMD – Extensions
•  Simple event-based programming model
•  Clean separation between ACEMD and extension
–  Much easier ...
TCL Extension Example
• 

Set thermostat parameters

• 
• 

Enable tclforces
Set annealing parameters

• 

Frequency of ca...
Plugin Example (1)
• 

Include API definition

• 

Set default values

• 

Initialisation function:
– 

• 

Parse vlaues fr...
Plugin Example (2)
Compile:

Configure in input file:

www.acellera.com
Metrocubo
• 
• 
• 
• 
• 

Patent pending

4 GPU workstation designed for ACEMD
Compact, quiet chassis
E3 Xeon CPU
Operatin...
ACEMD Test Drive
•  One week of access to a 4-GPU Metrocubo
•  Test ACEMD with your current models
•  Expert support for s...
ACECloud
•  Run ACEMD easily on Cloud resources
–  No need to deal with queuing systems
–  All files copies transparently

...
ACECloud
Run a simulation on the cloud:

See the progress of all simulations:

Patent pending

www.acellera.com
In-silico binding assays @ Acellera
•  We performed the calculations on 30 ligands in
45 days (1600 GPU days using aceclou...
http://htmdworkshop.wordpress.com

www.acellera.com
Any Questions?
Write to: 
info@acellera.com

www.acellera.com
GPU Accelerated Apps Momentum
Key codes are GPU Accelerated!

Molecular Dynamics
"
"
"
"
"
"
"
"
"

 
 
 
 
 
 
 
 
 

Aba...
Test Drive K20 GPUs!
Experience The Acceleration

Run ACEMD on Tesla K20 GPU
today

Sign up for FREE GPU Test Drive
on rem...
Test Drive K20 GPUs!

Questions?

Experience The Acceleration

Run ACEMD on Tesla K20 GPU
today

Sign up for FREE GPU Test...
Upcoming GTC Express Webinars
July 30 - Getting Started with GPU-accelerated Computer
Vision using OpenCV and CUDA
July 31...
GTC 2014 Call for Submissions
Looking for submissions in the fields of
§  Science and research
§  Professional graphics
...
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ACEMD: High-throughput Molecular Dynamics with NVIDIA Kepler GPUs

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Acellera Founder Gianni De Fabritiis, and CTO Matt Harvey talk about the latest developments of high-throughput molecular dynamics both in terms of applications and methodological advances. Examples are in the context of ACEMD, a highly efficient, best-in-class graphical processing units (GPUs) centric code for running MD simulations, and its protocols. In particular, attendees will learn how the high arithmetic performance and intrinsic parallelism of the latest NVIDIA Kepler GPUs can offer a technological edge for molecular dynamics simulations. Try GPUs for free via: www.Nvidia.com/GPUTestDrive

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ACEMD: High-throughput Molecular Dynamics with NVIDIA Kepler GPUs

  1. 1. ACEMD: HIGH-THROUGHPUT MOLECULAR DYNAMICS WITH NVIDIA KEPLER GPUS info@acellera.com www.acellera.com
  2. 2. -  M. Harvey, G. Giupponi and G. De Fabritiis, ACEMD: Accelerating biomolecular dynamics in the microsecond time scale, J. Chem. Theory and Comput. 5, 1632 (2009). -  M. J. Harvey and G. De Fabritiis, An implementation of the smooth particle-mesh Ewald (PME) method on GPU hardware, J. Chem. Theory Comput., 5, 2371–2377 (2009). www.acellera.com
  3. 3. Paradigms of molecular dynamics High performance! •  A single or few simulations run for very long •  Reached simulations time of several milliseconds •  Best systems: Anton, Desmond •  A bit easier to analyze High-throughput! •  Very many runs of reasonable length (hundreds of ns) •  Reached simulations time of several milliseconds •  Best systems: GPUs clusters, GPUGRID.net, Folding@home •  Complex analysis www.acellera.com
  4. 4. Binding processes Direct! A+B   Intermediate! AB   A+B   www.acellera.com AB*   AB  
  5. 5. SH2-pYEII •  T. Giorgino, I. Buch and G. De Fabritiis, J. Chem. Theory Comput.,8, 1171– 1175 (2012). www.acellera.com
  6. 6. FAAH-AEA •  E. Dainese, G. De Fabritiis et al. submitted (2013). www.acellera.com
  7. 7. IN-SILICO LIGAND BINDING Trypsin-Benzamidine I. Buch, T. Giorgino and G. De Fabritiis,Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations, PNAS 108, 10184-10189 (2011). www.acellera.com
  8. 8. Free ligand binding simulations! 35,000 atoms 500 trajectories 100 ns/each 50 µs of data Beta-Trypsin/Benzamidine (3PTB) ACEMD software AMBER99SB ff. Explicit solvent www.acellera.com
  9. 9. Calculating kinetics of binding Assuming first order kinetics www.acellera.com Guilliain Singhal N et al. J Chem Phys (2004) F and Thusius D. J Am Chem Soc (1970)
  10. 10. Characteristic transition modes www.acellera.com
  11. 11. Trypsin-benzamidine from X-ray a)  Poses of Benzamidine on Trypsin detected through high pressure x-ray crystallography b)  and c) The native binding pose of Benzamidine on Trypsin d)  Benzamidine poses labeled from X0-X8 on the front and back side of Trypsin www.acellera.com
  12. 12. FBDD ON FACTOR XA With Noelia Ferruz Capapey (Universitat Pompeu Fabra) Matt Harvey (ACELLERA), Jordi Mestres (IMIM) www.acellera.com
  13. 13. S1   S4   [1] Lee Fielding ,  Dan Fletcher ,  Samantha Rutherford ,  Jasmit Kaurand,  Jordi Mestres. Exploring the active site of human factor Xa protein by NMR screening of small molecule probes. Royal Society of Chemistry 2003. www.acellera.com
  14. 14. Library of compounds 34 compounds screened by STD-NMR 9 ligands bound to factor Xa 4 ligands selected for further studies www.acellera.com
  15. 15. Three derived by known inhibitors www.acellera.com
  16. 16. Experimental competition assays with TPAM •  Binding sites positions were hypothesized from similarity to known ligands: •  Ligands 29, 31 at site S1, •  Ligands 10, 27 at site S4. •  Displacement for ligands 10 and 29, but only partially to 27 and no displacement for 31. Ligand Predicted Pose Displacement Further comments 31 S4 No 29 S1 Yes - 27 S4/core Yes Only partially displaced 10 S4 Yes Highest affinity but not displacement Bad fit in experimental www.acellera.com curves
  17. 17. METHODS •  34 ligands built, simulated by MD and analyzed b means of Markov State Models •  Protein structure from human Factor Xa (2BOK[2]) was established as the initial protein conformation •  Each box contained only one randomly placed ligand giving a final concentration of 0.0038M •  1000 replicas of 50 ns were run for each system for an aggregate of 1.8 ms simulation data. www.acellera.com
  18. 18. Kinetics and thermodynamics Ligand Kd (µM) Residence Time (ns.) ∆G (kcal/mol) kon(s-1·M) koff (s-1) 29 126.9 ± 56.9 74786 ± 15914 -5.35 ± 0.2 (1.17 ± 0.07) ·108 (1.46 ± 0.63) ·104 15 363.1 ± 12.6 113445 ± 3637 -4.69 ± 0.0 (2.43 ± 0.00) ·107 (8.82 ± 0.23) ·103 16 1089.9± 659.1 87491 ± 12875 -4.10 ± 0.2 (1.23 ± 2.81) ·107 (1.19 ± 0.34) ·104 31 1543.5 ± 432.3 11165 ± 2623 -3.86 ± 0.2 (6.33 ± 1.09) ·107 (9.38 ± 1.83) ·104 -3.76 ± 0.0 (7.33 ± 0.40) ·10 6 (1.27 ± 0.07) ·104 (9.26 ± 0.11) ·10 6 (1.90 ± 0.00) ·104 7 (7.49 ± 2.09) ·104 27 1736.7 ± 119.3 78895 ± 3783 10 2047.3 ± 24.1 3 2056.7 ± 699.5 19753 ± 26094 -3.72 ± 0.3 (3.68 ± 0.35) ·10 13 3045.3 ± 1375.8 48332 ± 57242 -3.51 ± 0.3 (9.38 ± 7.20) ·107 (3.80 ± 3.04) ·105 23 5404.1 ± 2531.3 9673 ± 21216 -3.34 ± 0.8 (1.35 ± 4.27) ·108 (7.23 ± 3.88) ·105 12 9199.3 ± 1026.4 1959 ± 313 -2.78 ± 0.1 (5.65 ± 0.18) ·107 (5.20 ± 0.64) ·105 -2.61 ± 1.4 (1.21 ± 1.89) ·10 7 (9.43 ± 4.53) ·103 7 (2.94 ± 0.06) ·106 21 12126 ± 10080 52773 ± 50 -3.67 ± 0.0 162406 ± 117707 11 27013 ± 2511 340 ± 7 -2.14± 0.1 (1.10 ± 0.11) ·10 28 28500 ± 1844 1092 ± 67 -2.11 ± 0.1 (3.23 ± 0.03) ·107 (9.19 ± 0.54) ·105 7 29433 ± 1331 294 ± 11 -2.09 ± 0.1 (1.16 ± 0.02) ·108 (3.40 ± 0.13) ·106 20 34626 ± 5960 1625 ± 274 -2.00 ± 0.0 (1.83 ± 0.01) ·107 (6.33 ± 1.15) ·105 -1.94 ± 0.0 (1.01 ± 0.05) ·10 8 (3.82 ± 0.06) ·106 (1.56 ± 0.27) ·10 8 (6.28 ± 0.15) ·106 7 (2.16 ± 0.38) ·106 8 37980 ± 1505 261 ± 3 32 42040 ± 11404 26 60353 ± 11699 478 ± 89 -1.67 ± 0.1 (3.59 ± 0.09) ·10 2 92553 ± 27598 1697 ± 923 -1.44 ± 0.2 (1.52 ± 1.79) ·107 (1.78 ± 2.52) ·106 33 102180 ± 93464 1142 ± 365 -1.48 ± 0.3 (1.21 ± 0.07) ·107 (1.30 ± 1.35) ·106 25 123000 ± 5773 544 ± 3 -1.24 ± 0.0 (1.50 ± 0.06) ·107 (1.84 ± 0.01) ·106 -1.18 ± 0.0 (4.44 ± 0.11) ·10 7 (6.04 ± 0.22) ·106 7 (1.85 ± 0.02) ·106 6 136133 ± 4224 159 ± 3 165 ± 6 -1.89 ± 0.1 5 137467 ± 4224 540 ± 5 -1.17 ± 0.0 (1.35 ± 0.03) ·10 1 157133 ± 3930 627 ± 0 -1.10 ± 0.0 (1.01 ± 0.00) ·107 (1.59 ± 0.00 ) ·106 19 157333 ± 805 673 ± 28 -1.10 ± 0.0 (9.44 ± 0.02) ·106 (1.49 ± 0.06) ·106 4 210333 ± 6609 169 ± 24 -0.92 ± 0.1 (2.84 ± 0.06) ·107 (5.98 ± 0.70) ·106 17 238333 ± 23561 376 ± 21 -0.88 ± 0.2 (1.21 ± 0.26) ·107 (2.67 ± 0.15) ·106 -0.77 ± 0.0 7 (2.83 ± 0.07) ·106 18 270400 ± 93196 353± 8 (1.05 ± 0.00) ·10 7 (4.60 ± 0.01) ·106 30 345600 ± 8073 217 ± 0 -0.63 ± 0.0 (1.33 ± 0.00 ) ·10 22 464667 ± 1143 605 ± 0 -0.45 ± 0.0 (3.56 ± 0.03) ·106 (1.65 ± 0.00) ·106 24 539400 ± 3960 144 ± 3 -0.37 ± 0.0 (1.28 ± 0.02) ·107 (6.90 ± 0.18) ·106 14 658867 ± 105204 90 ± 1 -0.26 ± 0.1 (1.73 ± 0.32) ·107 (1.10 ± 0.02) ·107 -0.07 ± 0.0 (8.03 ± 0.32) ·10 6 (7.12 ± 0.12) ·106 (8.59 ± 0.11) ·10 6 (1.00 ± 0.02) ·107 9 34 887000 ± 22518 1172000 ± 33704 140 ± 2 99 ± 2 0.09 ± 0.0 www.acellera.com
  19. 19. www.acellera.com
  20. 20. LIGAND 27 Experimental results! •  •  Computational results! Weakly displaced by TPAM. Hypothesized to bind at S4 pocket by similarity with Berlex compound •  Binds at the core part of the cavity and entrance of S1 www.acellera.com
  21. 21. www.acellera.com
  22. 22. LIGAND 10 Experimental results! •  •  Computational results! Clearly displaced by TPAM. Expected to bind at pocket S4 by similarity with Rhone-Poulec Rorer compound. •  Binds at pocket S4 •  Sixth in ranking by KD www.acellera.com
  23. 23. LIGAND 29 Experimental results! •  •  Computational results! Clearly displaced by TPAM. Hypothesized to bind at S1 pocket by similarity with DuPont compound •  Binds at pocket S1 www.acellera.com
  24. 24. LIGAND 31 Experimental results! •  •  •  Computational results! KD = 30µM Failure to be displaced by TPAM. Expected to bind at S1 pocket becouse of the known high affinity of the S1 pocket for the amidine fragment •  Binds beneath the loop between S1 & S4 www.acellera.com
  25. 25. Ensemble view with TPAM www.acellera.com
  26. 26. METHODS From hardware to software www.acellera.com
  27. 27. “Molecular simulation will mature within the next 5 years to allow simulations at temporal scales of biological interest, thus achieving its full potential for biological discovery” 27 www.acellera.com
  28. 28. ACEMD - History •  Developed from CellMD (2006), 19 times a CPU •  First CUDA GPUs released 2006 •  ACEMD released 2007 •  First fully-GPU accelerated MD application •  First GPU implementation of Particle Mesh Ewald doi:10.1021/ct900275y •  Presented in ACEMD: Accelerating Biomolecular Dynamics in the microsecond time scale, JCTC 2009 doi:10.1021/ct9000685 www.acellera.com
  29. 29. ACEMD - Capabilities ACEMD has all the features required for production simulations of biomolecules: •  •  •  •  Major force fields: CHARMM, Amber, OPLS and Martini Common file formats: PDB, Bincoor, PRMTOP, PSF, DCD, XTC PME or GRF electrostatics NVE, NVT, NPT ensembles –  Langevin thermostat –  Berendsen barostat •  •  •  •  Constraints, restraints Powerful scripting and extension capability Multi-host execution for replica-exchange methods Binary distribution – no compilation necessary www.acellera.com
  30. 30. ACEMD - Resources User manual Extensions developer manual Protocols manuals Support forum for everybody support@acellera.com for paying users Develop for you to allow to interface your methods as plugins (almost always free) •  Acecloud – acemd cloud •  Metrocubo – acemd special patented hardware •  •  •  •  •  •  www.acellera.com
  31. 31. ACEMD - Performance DHFR   Exceptional single GPU performance Parallel scaling up to 1.4x on 3 GPUs (single host) Titan  OC   System sizes up to ~1M atoms Performance scales ~linearly with system size and GPU speed Does not need a GPU with fast double-precision arithmetic Does not need a fast CPU; performance normally dependent on GPU GTX780   ns/day   Tesla  K20,  GTX680   Tesla  M2090,  GTX  580   0   •  •  50   100   150   200   250   Benchmarking conditions: DHFR model (23558 atoms) NVT cutoff 9A, PME enabled (frequency 2), dt=4fs. Langevin thermostat System: 4 GPUs, X79 chipset, CUDA 4.2, driver 310.44, CentOS 6 www.acellera.com
  32. 32. ACEMD – Free basic download •  Optimal if you do little use of MD •  Have only single GPU machines in your lab •  Fully functional version of ACEMD on a single GPU •  Ideal for small groups or to start on MD •  http://www.acellera.com/acemd www.acellera.com
  33. 33. ACEMD - Extensions •  ACEMD can be extended by the user •  TCL – coded directly in input file •  Plugins – separate binary library •  Pros: •  Pros: –  Fast to develop –  Very familiar for NAMD users •  Cons: –  Slow for numerically intensive work –  Not all features exposed –  Only one TCL extension at a time •  –  Written in C or C++ –  Fast for numerically intensive work –  More advanced features than TCL interface –  Have multiple plugins active simultaneously Suitable for: –  Applying point restraints –  Modification of simulation parameters (eg temperature annealing) •  Cons: –  Written in C or C++ •  Suitable for: –  Writing complex, intensive plugins –  Interfacing with existing, third-party code www.acellera.com
  34. 34. ACEMD – Extensions •  Simple event-based programming model •  Clean separation between ACEMD and extension –  Much easier and safer to develop for than direct sourcecode modification •  Documented API with examples •  Events: –  –  –  –  Initialise called once at the beginning of the simulation Calcforces called every iteration during force evaluation Endstep called at the end of every iteration Terminate called once at the end of the simulation www.acellera.com
  35. 35. TCL Extension Example •  Set thermostat parameters •  •  Enable tclforces Set annealing parameters •  Frequency of calling extension •  Calcforces – called every* iteration –  Calculate new target temperature –  Apply new target temperature –  Disable extension when target temperature reached www.acellera.com
  36. 36. Plugin Example (1) •  Include API definition •  Set default values •  Initialisation function: –  •  Parse vlaues from arguments passed in the input file Calcforces called every* iteration –  Apply new target temperature www.acellera.com
  37. 37. Plugin Example (2) Compile: Configure in input file: www.acellera.com
  38. 38. Metrocubo •  •  •  •  •  Patent pending 4 GPU workstation designed for ACEMD Compact, quiet chassis E3 Xeon CPU Operating System and ACEMD installed Best price/performance for MD www.acellera.com
  39. 39. ACEMD Test Drive •  One week of access to a 4-GPU Metrocubo •  Test ACEMD with your current models •  Expert support for system setup and testing •  http://www.acellera.com/products/metrocubo/metrocubo-test-drive/ www.acellera.com
  40. 40. ACECloud •  Run ACEMD easily on Cloud resources –  No need to deal with queuing systems –  All files copies transparently •  Simple command-line interface –  optimised for managing large numbers of simulations –  Supports many users •  Test drive now: info@acellera.com Patent pending www.acellera.com
  41. 41. ACECloud Run a simulation on the cloud: See the progress of all simulations: Patent pending www.acellera.com
  42. 42. In-silico binding assays @ Acellera •  We performed the calculations on 30 ligands in 45 days (1600 GPU days using acecloud) •  Determined 4 strong fragments by residence time and another small group as intermediates, the others discarded •  Poses available for follow-up •  Pathway of binding •  Currently performing NMR on top molecules www.acellera.com
  43. 43. http://htmdworkshop.wordpress.com www.acellera.com
  44. 44. Any Questions? Write to: info@acellera.com www.acellera.com
  45. 45. GPU Accelerated Apps Momentum Key codes are GPU Accelerated! Molecular Dynamics " " " " " " " " "                   Abalone – GPU only code ACEMD – GPU only code AMBER CHARMM DL_POLY GROMACS HOOMD-Blue – GPU only code LAMMPS NAMD Quantum Chemistry " " " " " " " " "   ABINIT BigDFT   CP2K   GAMESS   Gaussian – in development NWChem   Quantum Espresso TeraChem – GPU only code   VASP Check many more apps at www.nvidia.com/teslaapps
  46. 46. Test Drive K20 GPUs! Experience The Acceleration Run ACEMD on Tesla K20 GPU today Sign up for FREE GPU Test Drive on remotely hosted clusters www.nvidia.com/GPUTestDrive
  47. 47. Test Drive K20 GPUs! Questions? Experience The Acceleration Run ACEMD on Tesla K20 GPU today Sign up for FREE GPU Test Drive on remotely hosted clusters www.nvidia.com/GPUTestDrive Contact us "   Devang Sachdev - NVIDIA " dsachdev@nvidia.com "   @DevangSachdev "   Acellera ltd " info@acellera.com Stream other webinars from GTC Express: http://www.gputechconf.com/page/ gtc-express-webinar.html    
  48. 48. Upcoming GTC Express Webinars July 30 - Getting Started with GPU-accelerated Computer Vision using OpenCV and CUDA July 31 - NMath Premium: GPU-accelerated Math Libraries for .NET August 7 - Accelerating High Performance Computing with GPUDirect RDMA Register at www.gputechconf.com/gtcexpress
  49. 49. GTC 2014 Call for Submissions Looking for submissions in the fields of §  Science and research §  Professional graphics §  Mobile computing §  Automotive applications §  Game development §  Cloud computing Submit at www.gputechconf.com

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