Jacket HPC

鴻鵠國際為台灣區JACKET代理商,同時也是NVIDIA GPU在台灣的代理商。

針對此產品教育訓練以及任何諮詢 請來電 廖先生 0917-782-811 terence@honghutech.com

Jacket HPC

Jacket HPC

Multi-GPU Option - Multiple Nodes

Jacket HPC delivers unprecedented ability to transparently scale GPU computing across cluster. When a single host is not capable of driving more GPUs, simply add GPUs to another host on the network and Jacket HPC will take care of the rest. CPU clusters may be upgraded through the installation of GPUs, significantly increasing the cluster's computational capability without investing in new development for specialized GPU code.

Jacket HPC is targeted at the GPU cluster market. Distributed clusters of GPUs, that contain more than eight (8) GPUs, are well suited for Jacket HPC.

多GPU的選項 - 多個節點

Jacket HPC提供前所未有的能力,透明地攀越GPU計算集群。當一台主機上不能夠帶動更多的GPU,只需添加GPU到另一台網絡上的主機使Jacket HPC將採取其餘的照顧。通過安裝的GPU可升級CPU集群,并提高集群的計算能力,而无需投資新開發的GPU代碼。

Jacket HPC是針對 GPU集群市場。分佈式集群的GPU,包含超過八個(8)圖形處理器,非常適合Jacket HPC。

Jacket HPC is built atop the Parallel Computing Toolbox (PCT) and Distributing Computing Server (DCS). PCT and DCS product licenses are required for executing Jacket HPC on network based HPC resources. With the addition of parallel constructs, such as PARFOR and SPMD, pre-existing code may be dispatched across all GPUs and CPUs in a cluster or a Cloud service. In many cases, little to no code revision is required to take advantage of this parallel computing capability.

Jacket HPC構建在並行計算工具箱(Parallel Computing Toolbox- PCT)和分佈式計算服務器(Distributing Computing Server - DCS)上。PCT和DCS產品都需要許可證才能執行Jacket HPC在基於HPC網絡資源。並行結構,如PARFOR和spmd,既存的代碼可以被派往所有在一個集群或雲服務的GPU和CPU。在許多情況下,幾乎不需要更改代碼就可以採取這種並行計算能力的優勢。

Executing large scale codes with Jacket HPC and GPU clusters can dramatically accelerate time to solution while minimizing the programming time associated with leveraging these resources. For workstations or personal supercomputers, with 2 to 8 GPUs, Jacket MGL provides the functionality to fully leverage these resources.

使Jacket HPC和GPU集群執行大規模的代碼可以大大加快時間需要得到解決方案,同時最大限度地減少利用這些資源的編程時間。2至8 GPU的工作站或個人超級計算機,Jacket MGL提供的功能可以充分利用這些資源。