OS
HPE Q7G75A NEC Vector Engine Accelerator Module
Manufacturer: HPE
UPC: 190017212005
SKU: Q7G75A
Condition: New
HPE Q7G75A NEC Vector Engine Accelerator Module
Product TypeVector Engine Accelerator
Brand NameHPE
ManufacturerHewlett Packard Enterprise
Product NameNEC Vector Engine Accelerator Module
Manufacturer Website Addresshttp://www.hpe.com
Application/UsageServer
Height1.5"
Width10.5"
Depth4.4"
Form FactorPlug-in Card
Weight (Approximate)2.60 lb
Are you looking for a mean to unleash your memory bandwidth bounded applications? The NEC Vector Engine Accelerator with its unmatched memory bandwidth per core offers a balanced architecture for your Fortran and C/C++ codes to shine. Extremely large amount of data can be processed per cycle thanks to the native vector architecture. Moreover, users can easily exploit these capabilities via a standard development environment leveraged from the past decades of the vector supercomputers era. What's new Vector processor system in a PCIe form factor hosted by a standard x86 server running a Linux® operating system as the user front end. Developed using 16nm FinFET process technology for extreme high performance and low power consumption. Exceptional integration of six HBM2 memory modules and vector processor using Chip-on-Wafer-on-Substrate technology, leading to an outstanding memory bandwidth of 1.2 TB/s. Features High Memory Bandwidth The NEC Vector Engine Accelerator has six integrated HBM2 modules providing 48 GB capacity and 1.2 TB/s bandwidth. Shared last level cache between the eight cores, facilitating shared memory parallelization. Standard Programming Environment The NEC Vector Engine Accelerator does not require users to migrate their applications to a new programming environment. Existing Fortran and C/C++ codes will not have to be ported but simply recompiled for the NEC Vector Engine processor. Full software environment is available with compilers, libraries and tools, leveraged from decades of experience with vector machines. Compilers are able to vectorize and auto-parallelize loops. Parallelization with OpenMP and MPI is supported.