Bitfusion Welcomes Samsung as a Strategic Investor
June 12, 2018
Sunnyvale, CA, June 12, 2018 — Bitfusion, the Elastic AI Software Platform, today announced that Samsung Ventures has made a strategic investment in Bitfusion and joined its board.
“Bitfusion Elastic Platform is a unique solution that can offer flexibility as well as Opex and Capex savings for deploying artificial intelligence (AI) and machine learning workloads. It also maximizes utilization and performance metrics across heterogeneous GPU clusters,” said Thomas Jueng, investment director in Samsung Venture Investment Corporation.
“We are delighted to welcome Samsung to the Bitfusion Board,” said Michael Zimmerman, Bitfusion CEO. “Bitfusion is offering companies a way to make efficient use of their GPU servers across their organizations – maximizing resources and reducing costs. With the support of a key AI industry player such as Samsung, we see a unique opportunity for deploying and optimizing our AI attached network software for wide use in the private and public clouds.”
About Samsung Venture Investment Corporation:
Samsung Venture Investment Corporation manages investment and investment-related activities for Samsung affiliate companies. The investment mandate for Samsung Venture Investment Corporation tracks closely to the strategic priorities of Samsung affiliate companies’ core operating divisions, and encompasses investments in semiconductors, displays, telecommunications, and consumer electronics.
AI and machine learning are changing every aspect of the data center. GPUs (and soon newer purposed-built AI hardware) are deployed at scale in Enterprises to accommodate newer workloads. However, unlike storage, compute and networking, GPUs are deployed in a scattered, siloed and uncoordinated way across the Enterprise. It drives negative metrics of productivity, profitability, Capex, Opex and agility. With Bitfusion, GPUs can be deployed as a shared and common pool, responding in real time to any demand of a machine learning workload. Bitfusion virtualizes the GPU cluster (of any size) by allowing any workload to remotely (over Ethernet) attach to a partial GPU, one or more GPUs anywhere in the cluster, for only the duration of the runtime code. See: www.bitfusion.io
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