The High Performance Conjugate Gradients (HPCG) benchmark is designed to measure performance that is representative of modern scientific applications relying on discretizations of Partial Differential Equations (PDEs). It does so by exercising the computational and communication patterns commonly found in real science and engineering codes, which are often based on sparse iterative solvers with complex multi-level preconditioners. HPCG exhibits the same irregular accesses to the main memory and fine-grain recursive computations that dominate large-scale scientific workloads used to simulate complex physical phenomena.
The HPCG 3.1 reference code was released in March of 2019. In addition to bug fixes, this release positioned HPCG to even better represent modern PDE solvers and made it easier to run HPCG on production supercomputing installations. The reference version is accompanied by multiple binary or source code releases from AMD, ARM, Intel, and NVIDIA, which are carefully optimized for the these vendors’ respective hardware platforms. The current HPCG performance list was released at SC21 and now features over 200 entries from across the supercomputing landscape. HPCG results have also been tracked by TOP500.org since June of 2017.
Find out more at http://www.hpcg-benchmark.org
In Collaboration With
- Sandia National Laboratories