HPCG - June 2023

The TOP500 list has incorporated the High-Performance Conjugate Gradient (HPCG) benchmark results, which provide an alternative metric for assessing supercomputer performance. This score is meant to complement the HPL measurement to give a fuller understanding of the machine.

  • Supercomputer Fugaku remains the leader on the HPCG benchmark with 16 PFlop/s.

  • The DOE system Frontier at ORNL claims the second position with 14.05 HPCG-Pflop/s.

  • The third position was captured by the upgraded LUMI system with 3.40 HPCG-petaflops.

 

Rank TOP500 Rank System Cores Rmax (PFlop/s) HPCG (TFlop/s)
1 2 Supercomputer Fugaku - Supercomputer Fugaku, A64FX 48C 2.2GHz, Tofu interconnect D, Fujitsu
RIKEN Center for Computational Science
Japan
7,630,848 442.01 16004.50
2 1 Frontier - HPE Cray EX235a, AMD Optimized 3rd Generation EPYC 64C 2GHz, AMD Instinct MI250X, Slingshot-11, HPE
DOE/SC/Oak Ridge National Laboratory
United States
8,699,904 1,194.00 14054.00
3 3 LUMI - HPE Cray EX235a, AMD Optimized 3rd Generation EPYC 64C 2GHz, AMD Instinct MI250X, Slingshot-11, HPE
EuroHPC/CSC
Finland
2,220,288 309.10 3408.47
4 4 Leonardo - BullSequana XH2000, Xeon Platinum 8358 32C 2.6GHz, NVIDIA A100 SXM4 64 GB, Quad-rail NVIDIA HDR100 Infiniband, EVIDEN
EuroHPC/CINECA
Italy
1,824,768 238.70 3113.94
5 5 Summit - IBM Power System AC922, IBM POWER9 22C 3.07GHz, NVIDIA Volta GV100, Dual-rail Mellanox EDR Infiniband, IBM
DOE/SC/Oak Ridge National Laboratory
United States
2,414,592 148.60 2925.75
6 8 Perlmutter - HPE Cray EX235n, AMD EPYC 7763 64C 2.45GHz, NVIDIA A100 SXM4 40 GB, Slingshot-10, HPE
DOE/SC/LBNL/NERSC
United States
761,856 70.87 1905.44
7 6 Sierra - IBM Power System AC922, IBM POWER9 22C 3.1GHz, NVIDIA Volta GV100, Dual-rail Mellanox EDR Infiniband, IBM / NVIDIA / Mellanox
DOE/NNSA/LLNL
United States
1,572,480 94.64 1795.67
8 9 Selene - NVIDIA DGX A100, AMD EPYC 7742 64C 2.25GHz, NVIDIA A100, Mellanox HDR Infiniband, Nvidia
NVIDIA Corporation
United States
555,520 63.46 1622.51
9 13 JUWELS Booster Module - Bull Sequana XH2000 , AMD EPYC 7402 24C 2.8GHz, NVIDIA A100, Mellanox HDR InfiniBand/ParTec ParaStation ClusterSuite, EVIDEN
Forschungszentrum Juelich (FZJ)
Germany
449,280 44.12 1275.36
10 23 Dammam-7 - Cray CS-Storm, Xeon Gold 6248 20C 2.5GHz, NVIDIA Tesla V100 SXM2, InfiniBand HDR 100, HPE
Saudi Aramco
Saudi Arabia
672,520 22.40 881.40

On the HPL-MxP (formally HPL-AI) benchmark, which measures performance for mixed- precision calculation, Frontier already demonstrated 9.95 Exaflops! The HPL-MxP benchmark seeks to highlight the use of mixed precision computations. Traditional HPC uses 64-bit floating point computations. Today we see hardware with various levels of floating point precisions, 32-bit, 16-bit, and even 8-bit. The HPL-MxP benchmark demonstrates that by using mixed precision during the computation much higher performance is possible (see the Top 5 from the HPL-MxP benchmark), and using mathematical techniques, the same accuracy can be computed with the mixed precision technique when compared with straight 64-bit precision.

Rank

HPL-MxP

Site

Computer

Cores

HPL-MxP (Eflop/s)

TOP500 Rank

HPL Rmax (Eflop/s)

Speedup

of HPL-MxP over HPL

1

DOE/SC/ORNL, USA

Frontier, HPE Cray EX235a

8,699,904

9.950

1

1.194

8.3

2

EuroHPC/CSC, Finland

LUMI, HPE Cray EX235a

2,174,976

2.168

3

0.3091

7.0

3

RIKEN, Japan

Fugaku, Fujitsu A64FX

7,630,848

2.000

2

0.4420

4.5

4

EuroHPC/CINECA, Italy

Leonardo, Bull Sequana XH2000

1,824,768

1.842

4

0.2387

7.7

5

DOE/SC/ORNL, USA

Summit, IBM AC922 POWER9

2,414,592

1.411

5

0.1486

9.5