IO Software for Exascale Architecture
Sector: Education • Location: France, Germany, United Kingdom, Ireland, Czechia, Sweden
Source: EU Funding & Tenders Portal
IO-SEA aims to provide a novel data management and storage platform for exascale computing based on hierarchical storage management (HSM) and on-demand provisioning of storage services. The platform will efficiently make use of storage tiers spanning NVMe and NVRAM at the top all the way down to tape-based technologies. System requirements are driven by data intensive use-cases, in a very strict c
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | ended |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | IO-SEA aims to provide a novel data management and storage platform for exascale computing based on hierarchical storage management (HSM) and on-demand provisioning of storage services. The platform will efficiently make use of storage tiers spanning NVMe and NVRAM at the top all the way down to tape-based technologies. System requirements are driven by data intensive use-cases, in a very strict co-design approach. The concept of ephemeral data nodes and data accessors is introduced that allow users to flexibly operate the system, using various well-known data access paradigms, such as POSIX namespaces, S3/Swift Interfaces, MPI-IO and other data formats and protocols. These ephemeral resources eliminate the problem of treating storage resources as static and unchanging system components – which is not a tenable proposition for data intensive exascale environments. The methods and techniques are applicable to exascale class data intensive applications and workflows that need to be deployed in highly heterogeneous computing environments. Critical aspects of intelligent data placement are considered for extreme volumes of data. This ensures that the right resources among the storage tiers are used and accessed by data nodes as close as possible to compute nodes – optimising performance, cost, and energy at extreme scale. Advanced IO instrumentation and monitoring features will be developed to that effect leveraging the latest advancements in AI and machine learning to systematically analyse the telemetry records to make smart decisions on data placement. These ideas coupled with in-storage-computation remove unnecessary data movements within the system. The IO-SEA project (EuroHPC-2019-1 topic b) has connections to the DEEP-SEA (topic d) and RED-SEA (topic c) project. It leverages technologies developed by the SAGE, SAGE2 and NextGEN-IO projects, and strengthens the TLR of the developed products and technologies. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
Article Published Date | Obfuscated Data |
