Model Whale

Model Whale,Heywhale community online data science tool,provides free GPU

Model Whale Official Website, Heywhale Online Data Science Tools, Offers Free GPU

What is Model Whale?

ModelWhale Cloud-based collaborative data science tool, helping to solve complex engineering, difficult data security application, difficult achievement transfer, and difficult achievement reproducibility. Based on different usage scenarios, ModelWhale provides three versions, namelyBasic, Professional, and Team Editions; In addition, we also providePrivate Cloud Independent Deployment Services! ModelWhale! Instantly available cloud-based data science collaboration tool

Model Whale Official Website 1:

https://www.heywhale.com/mw/workspace/index

Model Whale Official Website 2:https://www.modelwhale.com/pricing

Model Whale User Manual:https://www.heywhale.com/docs/org_admin/

ModelWhale. Data-driven research · Walk with pioneers! Heywhale's data science collaboration platform, deeply integrates functions such as data management, modeling analysis, model training management, computing resource management, and task management, solving issues like data security, complex engineering, and difficult achievement transfer and reproducibility for researchers and teams.
https://www.modelwhale.com/pricing

Using Jupyter Notebook locally can be costly and time-consuming, and you have to reinstall the original computing environment, experiencing the pain of package failure, insufficient memory, poor network, and compilation errors.

ModelWhale, however, is available for immediate use anytime, anywhere. If you need to change computing power, simply select the corresponding resources when running the project, saving time and effort without waste.

Powerful computing power scheduling and management capabilities

How to carry out computing power scheduling and management has always been a concern for many universities and research institutions. As mentioned earlier, the current situation is that due to the lack of a reasonable scheduling mechanism, there is a situation where powerful hardware resources are not used. This section will provide solutions from four levels: computing power access, unified management of various specifications of computing power, fine-grained computing power scheduling, and on-demand computing power resources.

Computing power access: Private cloud deployment and maintenance

For independently deployed ModelWhale, computing power access can choose local servers (the preferred choice for customers who need to efficiently utilize existing hardware equipment), private cloud, or cloud services provided by mainstream cloud vendors. Regardless of the method, ModelWhale, based on cloud-native technology solutions, can flexibly connect and support cross-cloud scheduling.

After deployment, ModelWhale will

provide full maintenance services and a complete after-sales mechanism,ensuring full tracking. General issues can be resolved remotely online; serious or complex issues can also be addressed locally, no longer wasting human resources of the research organization on system maintenance.Unified management of various specifications of computing power: No waste of idle computing power

If local servers of universities and research institutions are chosen to complete computing power access, this means that the computing power of local servers within the organization has been integrated. The next step is the unified management of various specifications of computing power, that is, how to make better use of the previous idle resources and allocate them to different teachers, research staff, and project teams.

Through ModelWhale, administrators of universities and research institutions can use the graphical operation interface,

to split computing power according to the number of cores and memory size, and then allocate it to different groups according to different usage needs.For example, large and complex computing tasks often occur in data-driven research, requiring higher specifications of CPU computing power or GPU clusters. Meanwhile, more basic computing power resources can be allocated to teaching teams within universities for course practice, ensuring that no computing power is idle.In addition, ModelWhale also provides a resource application mechanism. When the existing computing and storage resources are insufficient, project group administrators can directly initiate an application to obtain computing power supplements in a timely manner to meet different research needs.

Computing power resources are allocated to different research project groups as needed

Fine-grained and flexible computing power scheduling

If the focus of unified management of various specifications of computing power is on the organization from universities and research institutions to different project teams within the organization, then fine-grained and flexible computing power scheduling is more concerned about computing power allocation among team members.

Using computing power resources within a data-driven research project group is a "high specification + high concurrency" scenario. How to allocate limited computing power to a large number of researchers within the group? Just like the organization administrator, the project group administrator can also complete remote resource allocation and control through simple point-and-click operations, down to each member within the group, including configuring specific resource types and durations that can be used. Through computing power on the cloud,

researchers within the project group are no longer limited to the network or computers in the office or laboratory, and can conduct relevant research at any time and anywhere with their personal PCs.Computing resource management: See each student's computing power usage

Project group administrators and leaders' real-time control over the computing power of group members is also

a way to prevent resource waste.In addition, when computing power is scarce, ModelWhale not only provides a resource queuing mechanism but also supports configuring resource usage priority for group members to ensure that relatively important research work is completed first. Finally, the computing power application mechanism also applies to project teams, with applications reviewed by administrators and automatically allocated resources based on the needs of each researcher.Computing power resources are available on-demand

Finally, computing power, like analysis environments and images, is part of the on-demand availability: After obtaining the allocated computing power from the project group administrator, group members can independently select the required computing power before starting the project, and can

one-click complete resource callsto start data research work. At the same time, they can also check their own computing power, memory, and disk usage at any time during the research process. When encountering large and complex computing tasks, the newly launched Pipeline function can supporttask orchestration and parallel computing, which is part of the offline model training process and makes related computing power scheduling more efficient.Resources are automatically released after the project is closed and computing power usage is completedto be used by other researchers in the group as needed.Available for other researchers in the group to use.