Edgecore Networks and
TensorWave announced a partnership to provide cutting-edge high-efficiency
networking solutions. This strategic partnership aims to meet the
surging demands of TensorWave's AMD-powered AI data centers, enabling
seamless integration of advanced networking capabilities to support the
rapid growth of AI and ML workloads.
As AI and machine learning applications continue to evolve, the need for
high-performance networking solutions becomes increasingly critical.
With Edgecore Networks' expertise in open networking and TensorWave's
leadership in AI technology, this collaboration forms a significant
milestone in addressing the unique networking challenges faced by AI
data centers.
The cornerstone of this partnership is Edgecore Networks' AIS800 800G
switch with 64 800G OSFP or QSFP-DD800G ports, embedded with a powerful
Tomahawk5 high-performance, low-latency design. The exceptional
performance and reliability of the switch are essential in supporting AI
and machine learning workloads. This state-of-the-art switch has
undergone rigorous testing and validation, demonstrating its capability
to deliver the highest performance in modern AI data center networks.
"We are excited to partner with TensorWave and provide Edgecore's
advanced open networking solutions tailored to the specific needs of AI
data centers," said Andy Wu, Chairman and President of Edgecore
Networks. "Leveraging the leading AMD-powered AI/ML data center
technology from TensorWave and innovative 51.2T open networking
solutions provided by Edgecore, the collaboration will offer
unparalleled performance, scalability, and efficiency, empowering data
center operators to meet the demands of the AI revolution."
"We are excited to team up with Edgecore Networks to boost the
networking capabilities of our AMD-powered AI data centers," said
Darrick Horton, CEO of TensorWave. "With the combined expertise of
Edgecore Networks and TensorWave, our customers can look forward to
improved operational efficiency, reduced latency, and smooth integration
with their existing AI workflows."