Cypress: High Performance Computing System

The Tulane University High Performance Computing system, Cypress, is composed of Dell state-of-the-art technology, using Intel Ivy Bridge CPU, Intel Xeon Phi Coprocessor, and Lustre file system running on Dell storage with Intel Enterprise Edition for Lustre (IEEL) technology. The components of Cypress were carefully selected to provide consistent performance over a wide range of scientific applications. Cypress will deliver a peak general capability of 668.75TF and will incorporate 7.936TB of fast main memory with 1 Petabyte (1PB) of high-performance storage. Cypress is designed to provide a powerful but flexible design, suited to the computing resource demands of computational scientists and researchers.

For a sample of research projects made possible by Cypress and our HPC team, follow this link to see Tulane HPC Highlights.

The design of Cypress is very similar to larger machines that are deployed or being deployed at the Louisiana Optical Network Initiative (LONI) and the Texas Advanced Computing Center (TACC), making it easy for our researchers to port their code to larger environments as their models grow larger and more complex.

Our team holds periodic educational HPC workshops to introduce our research community to our HPC resources, and we are also available for consultation regarding your research projects.


Meet Our Team

Hideki Fujioka

Hideki Fujioka

Computational Scientist

Ph.D., Biomedical Engineering (1997)
Keio University, Yokohama, Japan

M.S., Biomedical Engineering (1995)
Keio University, Yokohama, Japan

B.S.E., Mechanical Engineering (1993)
Keio University, Yokohama, Japan

Hoang Tran

Hoang Tran

HPC Administrator

Ph.D., Biomedical Engineering (2007)
Washington University in St. Louis, St. Louis, MO

B.S.E., Biomedical Engineering (2002)
Tulane University, New Orleans, LA

Carl Baribault

Carl Baribault

Computational Scientist

Dr. Carl Baribault holds a PhD in Engineering and Applied Science from University of New Orleans, and master’s degrees in mathematics (UT-Austin) and physics (UNC-Chapel Hill). His computer science background includes bioinformatics, structural eukaryotic gene prediction, and genomic and epigenomic data analysis. Dr. Baribault served as post-doctoral fellow on the genomics analysis core team at Tulane Cancer Center supporting multiple principal investigators in experimental design and various computational needs. He also has broad experience in software development for engineering and business applications.

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