Your estimated system performance (Rmax) in GFLOPS based on an 84% system efficiency is: Note: You may also type in the actual (Rmax) obtained via HPL and find its rank and efficiency.
Your efficiency is:
You can also select a different Top500 list date and see where your system would have ranked in that list:
Your estimated rank in the selected Top500 list date is:
Your estimated rank in the coming Top500 list: Note: This is relative to the selected list date.

Below is the 100% theoretical system performance (Rpeak) in GFLOPS along with other common efficiencies:

70%	72%	74%	76%	78%	80%	82%	84%	86%	88%	90%	92%	94%	96%	98%	100% (Rpeak)
0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

Below are more details on how to actually run HPL on your system and some tuned parameters suggestions for the HPL input file:

Total number of processors in your grid: 0

Note: The shape of the grid should be close to being a "square", thus P and Q should be approximately equal, with Q slightly larger than P, and both are whole numbers (i.e. no decimals).

Possible combinations of how the HPL grid might look like in terms of P and Q:

P

x

Q

Note: Usually 90% of memory is a decent choice for N, while NB=224 was a good block size to use with our Infiniband clusters of size 128 and 512 nodes. If you choose a small value for N, this will result in not enough work performed on each CPU and will give you bad results and low efficiency. If you choose a value of N exceeding your memory size or a size that does not leave enough memory for the operating system processes to run, swapping will take place and the performance will go down.

Possible memory percentages (i.e. N values) aligned with various NB values:

N/NB	96	104	112	120	128	136	144	152	160	168	176	184	192	200	208	216	224	232	240	248	256
80%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
82%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
84%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
86%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
88%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
90%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
92%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
94%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
96%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
98%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
100%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

HPL Over MVAPICH HowTo (Running on a 512-nodes Infiniband Linux cluster) HPL Over Intel-MPI HowTo (Running on a 128-nodes Infiniband Linux cluster) HPL Using NVIDIA GPUs

Developed By: Mohamad Sindi

sindimo@alum.mit.edu