Surin has a history of development of advanced supercomputers, workstations, servers and cluster based on NVIDIA Tesla and NVIDIA Quadro® GPUs.
Surin has been selected as the supplier of Nvidia GPUs by many research and industrial centers.
Many of the most popular applications already feature GPU support. Your own applications may take advantage of GPU acceleration through several different avenues:
“Drop-in” GPU-accelerated libraries – provide high-speed implementations of the functions your application currently executes on CPUs.
OpenACC / OpenMP Compiler directives – allow you to quickly add GPU acceleration to the most performance critical sections of your application while maintaining portability.
CUDA integrated with C, C++ or Fortran – provides maximum performance and flexibility for your applications. Third-party language extensions are available for a host of languages, including Java, Mathematica, MATLAB, Perl and Python
Surin’s GPU-based solutions can help you use GPUs to accelerate your performance.
Turing or RTX is the latest Nvidia graphics processor architecture (GPU) built after the Volta architecture. The RTX architecture was first introduced in August 2018 with professional Quadro RTX GPUs and a week later with GeForce RTX graphics cards. The RTX architecture for the first time provides real-time ray tracing on graphic cards. The realization of this has long been one of the goals of the computer graphics industry. Key features of the RTX architecture include the AI processor (Tensor cores) and special ray tracing processors (RT cores). Turing uses Microsoft DXR, OptiX and Vulkan to operate beam tracing.
Unique features available in the latest NVIDIA GPUs include:
High-speed, on-die GPU memory
NVLink interconnect speeds up data transfers up to 10X over PCI-Express
Unified Memory allows applications to directly access the memory of all GPUs and all of system memory
Direct CPU-to-GPU NVLink connectivity on OpenPOWER systems supports NVLink transfers between the CPUs and GPUs
ECC memory error protection – meets a critical requirement for computing accuracy and reliability in data centers and supercomputing centers.
System monitoring features – integrate the GPU subsystem with the host system’s monitoring and management capabilities such as IPMI. IT staff can manage the GPU processors in the computing system with widely-used cluster/grid management tools.
To choose the right product, contact one of our experts and get a free consultation on Skype or click here to leave us a message.
At Surin we strive to maximize throughput with the right design and advice whilst maintaining the lowest possible cost for our customers.