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UNIVERSITY OF WATERLOO has floated a tender for Graham Storage Replacement. The project location is Canada and the tender is closing on 15 Apr 2024. The tender notice number is 24-038 TT, while the TOT Ref Number is 99015874. Bidders can have further information about the Tender and can request the complete Tender document by Registering on the site.
Procurement Summary
Country : Canada
Summary : Graham Storage Replacement
Deadline : 15 Apr 2024
Other Information
Notice Type : Tender
TOT Ref.No.: 99015874
Document Ref. No. : 24-038 TT
Competition : ICB
Financier : Self Financed
Purchaser Ownership : Public
Tender Value : Refer Document
Purchaser's Detail
Purchaser : UNIVERSITY OF WATERLOO
Ontario, CAN
Contact Information : Reception Services, 519-888-4501, procure@uwaterloo.ca, Terry Taylor, 5198884567 ext. 33982, terryt@uwaterloo.ca
Canada
Email :procure@uwaterloo.ca
Tender Details
The Graham cluster is a general-purpose resource for researchers from across Canada. It supports a very wide range of codes with diverse performance profiles. The cluster and storage are configured to run all planned workloads well, but it is not intended to be optimized for any specific subset of codes or users. Accelerated codes that use GPU cards include the standard AI/ML workloads, but MD codes and others make up most of the GPU demand. At any given time, the cluster will be executing a mixture of serial, MPI, OpenCL, CUDA, large memory, data intensive and interactive jobs. This RFP is to replace the storage systems associated with the cluster. A future RFP will be issued to replace the computing infrastructure.
Solicitation Type : RFP - Request for Proposal (Formal)
Reference Number : 0000266584
Location : Canada, Ontario
Description : The Graham cluster is a general-purpose resource for researchers from across Canada. It supports a very wide range of codes with diverse performance profiles. The cluster and storage are configured to run all planned workloads well, but it is not intended to be optimized for any specific subset of codes or users. Accelerated codes that use GPU cards include the standard AI/ML workloads, but MD codes and others make up most of the GPU demand. At any given time, the cluster will be executing a mixture of serial, MPI, OpenCL, CUDA, large memory, data intensive and interactive jobs. This RFP is to replace the storage systems associated with the cluster. A future RFP will be issued to replace the computing infrastructure.
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