SuperServer 1029GQ-TVRT Australia

SuperServer-1029GQ-TVRT supports Intel 2nd Gen Xeon Scalable family which drives greater efficiencies and lower TCO across the modernisation of infrastructures. The processor provides a foundation for enterprises, cloud, HPC, storage and communication applications.
This processor features:

Dual-socket systems are mainstream in data centres. Increased CPU cores and multithreading ultimately help build large scale-out systems and diversify applications for businesses and end users.
SuperServer-1029GQ-TVRT supports dual sockets processors which provides more cores and overall, more database tasks the system can handle. Dual processors are ideal for CPU intensive applications such as scientific applications, machine learning or deep learning, HPC, virtual machines and more.

SuperServer-1029GQ-TVRT supports the NVIDIA V100 Tesla, the most advanced data centre GPU in accelerating AI, high performance computing (HCP), data science and graphics. The GPU is powered by NVIDIA Volta architecture which offers 16GB or 32GB configurations, with performance of up to 100 CPUs in a single GPU. This is ideal for application from data scientists, researchers, and engineers.

SuperServer-1029GQ-TVRT features a 1U Rack server form factor designed to maximise rackspace and improve scalability with lower power consumption and TCO. This server is ideal for basic entry-level applications to high performance work loads.

SuperServer-1029GQ-TVRT can support up to 1.5TB of RAM provides sufficient RAM for many media projects such as video and audio editing, virtual machines, cloud computing and web hosting. This server is best suited for users that need high RAM storage to run their business.

SuperServer-1029GQ-TVRT is equipped with 2.5" SATA hot-swappable drive bays which allow for significantly better transfer speeds than traditional hard drives with ease of installiation and reduced size.

This system utilises a redundant power supply which refers to being powered by two or more physical power supplies. As a result, this improves system up-time as each power supply will have the capacity to run the system on its own if one were to fail.

SuperServer-1029GQ-TVRT is equipped with NVMe which is the next-generation solid state storage technology. The NVMe efficiently supports the needs of client systems and enterprises using PCIe SSD. NVMe delivers rapid access and consumes less power, thus being more cost efficient. NVMe reduces latency and delivers higher input/output per second, as well as offering high performance across multiple cores for users that need quick access to data, support for security protocols and scalability for current and future performance.

SuperServer-1029GQ-TVRT supports Dual 10-GigaBit Ethernet which delivers significantly fast data speeds, overall better hardware and rack space efficiency, simple virtualization capabilities , less cabling, and greater overall scalability.

SuperServer-1029GQ-TVRT is GPU optimised, which offloads the burden of demanding computational tasks from the CPU. This allows servers to manage intense computing, composed of multiple cores handling hundreds of threads-accelerating the application's speed dramatically over a CPU-only application. A GPU amplifies its bandwidth with cache memory, whereas a CPU uses cache to reduce memory access latency, costing a lot of dead-space. A GPU-Optimised server is best suited for processing complex algorithms and massive data set for computer science applications, virtualization, and engineering.

This system is highly compatible with VMware, a virtualization and cloud computing software that helps modernise your data centre for modern apps, multi-cloud, digital workspaces and even telco cloud. Discover more about VMware here.

Artificial intelligence (AI) requires purpose-built servers to handle data-intensive workloads — From data preparation to refined training models. This system is highly capable of handling artificial intelligence and machine learning use case. Delivering great compute performance and capacity to train and deploy AI/ML workloads quicker.