To be able to run on both CPU and GPU clusters, the examples will use the prepared orbitals in a HDF5 file.
Each run will have
* initialization : read from xml and hdf5, FFT transform using FFTW and set up interpolation table using einspline library
* Vmc : warmup block to generate DMC samples
* Dmc : this is the main computation section
Critical routines for the optimal performance are in src/einspline directory. Optimized HDF5 and FFTW libraries can improve the initialization performance.
However, the input parameters will be chosen so that the initialization is not critical for the overall performance, I.e., the time-to-solution.
Each example will use the fixed number of MC steps, I.e., blocks and steps are fixed.
Each team can choose the total workloads (samples) and the number of parallel processing units (MPI tasks and OpenMP threads). A minimum workload will be specified for each example.
I will post the updated instructions by Monday next week.
Bests,
Jeongnim
* QMCPACK operates in two very different computational regimes depending on the nodal approximation that is used: an analytic form (free particle nodes, atomic orbitals) vs. a DFT-derived dataset read in from file. To avoid having to optimize for all possible use cases, can any guidance be given as to which of these two types of systems we can expect?
* Will the number of steps and blocks be set at the outset, or is the expectation that teams will have to choose an appropriate number to achieve a given statistical error bar?
Thank you,
Jessica Dudoff
On Thursday, October 18, 2012 3:24:15 AM UTC-7,
jim8001...@gmail.com<mailto:
jim8001...@gmail.com> wrote:
Hi,
I would like to ask some questions of QMCPACK.
First question is that, is there any visualization application for QMCPACK?
I couldn't find it.
Second, there are several tutorials on the website of QMCPACK, but some examples of them can not use GPU to accelerate, will them appear in this competition? If they will, should we need to determine that which can use GPU to accelerate or not ?
Thanks
Jim Chen
--
You received this message because you are subscribed to the Google Groups "SCC12" group.
To post to this group, send email to
sc...@googlegroups.com<mailto:
sc...@googlegroups.com>.
To unsubscribe from this group, send email to
scc12+un...@googlegroups.com<mailto:
scc12+un...@googlegroups.com>.