Giga Computing Unveils Gigabyte R-Series Servers for Enhanced Cloud Performance

Introduction to Giga Computing’s New Servers

Giga Computing, a subsidiary of Gigabyte, has made a significant announcement today with the release of two enhanced performance servers: the R183-ZK0 and the R283-ZK0. These servers are designed to support data-intensive applications and cloud services with increased reliability and scalability.

High-Performance Capabilities

Both new models are equipped to support AMD EPYC 9004 processors and are ready for the upcoming fifth-generation AMD EPYC processors, offering up to 192 CPU cores. These servers are unique in the market for being single-node configurations with two CPUs that support 48 memory DIMMs, leveraging Gigabyte’s expertise in motherboard design and signal integrity. The R183-ZK0 and R283-ZK0 may respectively hold up to 12TB of memory using 256GB DDR5 3DS RDIMMs.

Innovative Cooling Solutions

The R183-ZK0 utilizes a direct liquid cooling (DLC) solution to ensure optimal performance and energy efficiency. This cooling technology, which includes Gigabyte’s own cold plate technology, is particularly beneficial for CPU and memory-intensive workloads, facilitating the processing of large datasets or hosting multiple virtual machines efficiently.

Traditional and Advanced Air Cooling

On the other hand, the R283-ZK0 employs an air cooling solution that fits seamlessly into existing data center infrastructures. With twelve 2.5″ storage bays for Gen 5 NVMe and SATA drives, this server is designed for the efficient management and access of large data volumes. Additionally, it incorporates a “zigzag” layout, providing users with various configuration and expansion options, resulting in a highly scalable memory capacity and performance.

Conclusion

With these new R-series servers, Giga Computing continues to push the boundaries of what’s possible in server technology. By offering advanced cooling solutions and high-performance capabilities, these servers are set to become key components in data-centric environments, ensuring efficient, reliable, and scalable operations.

Randee J. Ramos
Randee J. Ramos
Karafiátova 1878 798 41 Kostelec na Hané

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