1. GPGPU use cases from the MoBrain community
João Rodrigues
Postdoctoral Researcher
Utrecht University, NL

2. MoBrain main activities
Task 1: User support and training
Task 2: Cryo-EM in the cloud: bringing clouds to the data
Task 3: Increasing the throughput efficiency of WeNMR portals via DIRAC4EGI
Task 4: Cloud VMs for structural biology
Task 5: GPU portals for biomolecular simulations
Task 6: Integrating the micro (WeNMR/INSTRUCT) and macroscopic (NeuGRID4you) VRCs

3. Software our solutions
Powerfit
Fitting atomic structures in Cryo-EM density maps using a full exhaustive 6D cross-correlation search based on FFT techniques.
DisVis
Visualization and quantification of accessible interaction space of distance-restrained protein-protein docking based on FFT techniques.
GROMACS
Versatile package to perform Molecular Dynamics simulations on systems with hundreds to millions of particles.
AMBER
Package to perform Molecular Dynamics simulations.

4. Use Case fitting atomic structures in Cryo-EM density maps
Powerfit
Fitting atomic structures in Cryo-EM density maps using a full exhaustive 6D cross-correlation search based on FFT techniques.

5. Software powerfit & disvis
Core Dependencies
Numpy
Cython
Scipy

6. Software powerfit & disvis
Numpy
Cython
Scipy
Accelerated
CPU
FFTW3
pyFFTW

7. Software powerfit & disvis
OpenCL
pyOpenCL
clFFT
Numpy
Cython
gpyFFT
Scipy
GPGPU Acceleration
FFTW3
pyFFTW

8. Software powerfit & disvis

9. Use Case MD simulation of a large protein system
Ferritin is a protein of 450 kDa, consisting of 24 subunits
A MD simulation in explicit solvent involves:
more than 4000 amino acids
more than water molecules
Total atoms:
Test Simulations were run using
AMBER 14, with OpenMPI
Performance on 2 GPU K20m: 8.66 ns/day

10. Software GROMACS & AMBER
CUDA 4.x
MKL
CC & CMake
FFTW3

11. Software GROMACS & AMBER
CUDA 4.x
GBs of data per day per simulation.
MKL
CC & CMake
FFTW3

12. Queueing & Middleware resources & requirements
Example Hardware
Cluster based on 3 Worker Nodes:
2x XEON E v2
2x K20m
64 Gb RAM
Total
36 CPU core and 6 GPU 192 Gb RAM

13. Queueing & Middleware resources & requirements
OpenMPI
Middleware Requirements
One Job per GPU (AMBER)
CPUs must be powerful to match the GPU
CPU is still doing some work (e.g. bonded interactions)
Discoverable within the e-infrastructure (e.g. jdl requirement)
Preferrably containing GPU type (GTX vs K-series, AMD vs NVIDIA)
AMD GPUs not supported by MD code (yet)
Double-precision only supported by Tesla cards
Torque & Maui

14. Conclusions & Questions
OpenCL
Scipy
pyOpenCL
CUDA
CC & CMake
Numpy
clFFT
FFTW3
OpenMPI
Torque & Maui
gpyFFT
Cython
pyFFTW
MKL
Thank you for your attention