The Exascale Computing Project has concluded. This site is retained for historical references.

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ALPINE project tests novel algorithm for in situ exascale data analysis

Researchers working with the Exascale Computing Project (ECP) have demonstrated a novel moment invariant pattern detection algorithm to drive in situ pattern recognition during simulations running on high-performance computing architectures.

ECP-funded scientists examine Julia’s usefulness for quantum chemistry software development

Researchers working under the Exascale Computing Project have shown that JuliaChem, a quantum chemistry software written with the Julia programming language, can deliver effective performance, superior ease of use, and

CEED project examines scalability and performance of key algorithms for HPC applications

Researchers working with the Exascale Computing Project’s Center for Efficient Exascale Discretization recently published findings of investigations they conducted into performance trade-offs for compute-intensive kernels in scientific computing applications. Large-scale

Novel algorithm improves supervised learning training methods

Researchers funded by the Exascale Computing Project have developed a new algorithm that improves kernel ridge regression methods used for supervised learning problems. The low-rank compression algorithm, which exploits both

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