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Press release  2019.8.5

Fixstars Solutions accelerates brain-wide mesoscale circuit mapping in Cold Spring Harbor Laboratory

The high-end GPU cluster server system used by Cold Spring Harbor Laboratory (CSHL) was delivered by Fixstars Solutions; Fixstars Solutions also provided software consultation to utilize the GPUs.

Cambridge — August 2, 2019 — Fixstars Solutions, Inc., a US subsidiary of Fixstars Corporation, a global leader in multicore CPU, GPU and FPGA acceleration technology, today announced that it has completed the delivery of a cluster server system with 16 x NVIDIA RTX 2080Ti boards and 8 x 3.2 TB CM5 Enterprise NVMe SSDs to CSHL. CSHL was nominated as the No.1 institute in "Top 10 academic institutions in 2018" published by Nature [1] and is a private, non-profit institution with research programs focusing on cancer, neuroscience, plant biology, genomics, and quantitative biology.

Figure: Delivered cluster server system

Beginning work in early 2019, Fixstars Solutions, Inc. worked alongside Professor Partha Mitra, a researcher in the intelligent machines that are products of biological evolution, and his laboratory members to accelerate their image processing of mice and marmoset brains. One of the biggest issues in his research was the long processing time for the high-resolution microscope images. Fixstars Solutions, Inc. analyzed their software and concluded that they should be able to achieve at least 4-fold acceleration using this new system.

"I am very excited that our expertise in parallel programming techniques has enabled us to accelerate the software process for their brain-wide mesoscale circuit mapping in mice.", said Aki Asahara, CEO, Fixstars Solutions, inc. "We have been involved in this project since the research phase (on what hardware to use), and I believe that this new system with NVIDIA RTX2080Ti processors and Toshiba Memory CM5 NVMe SSDs is the best for their workload."

Fixstars will continue to accelerate Mitra lab's research through the provision of technical expertise in parallel processing.


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