Use your existing ICT infrastructure and improve AI/ML delivery with ActiveEon
With the growth of AI and ML, institutions are looking at federating their complex architecture, which is extremely hard to manage, not only in terms of IT operation itself but also in terms of budget and sharing the infrastructure across all silos.
Take advantage of your existing infrastructure
One key element with the ProActive solution is that the compute infrastructure, data, and applications are equally accessible to staff, faculty, researchers, and students, but with different permissions and front ends.
|Unify All compute resources||Integrate all AI/ML tools|
|Automate IT operation||Keep existing tools|
Crunch these demanding AI/ML workloads
While AI workloads share some similarities to other workloads, AI processing requires more speed and access to multiple platforms.
Every core within your entire physical, virtual, and cloud infrastructure is automatically monitored in real-time with the orchestration tool. ProActive orchestrates tasks distribution in parallel across all available cores, making sure to speed up these demanding AI/ML workloads.
If a specific workload needs more compute resources and within individual rights, the solution can automatically provision cloud instances. It will also terminate instances as soon as the workload is finished. The provisioning and termination of these instances are managed within the set of policies defined by the IT department, ensuring that SLA is never breached.
OUT-OF-HOURS AVAILABLE COMPUTE RESOURCES
Take advantage of having a centralized solution and make "out of hours" idled or underutilized classroom computers working for you. The orchestration will detect idle computers and, if allowed, will use them for processing these hungry AI model's training. In the morning, you might discover that you do not need to buy new computers that urgently.
Empower AI/ML Teaching/Research
Imagine a better way to share AI/ML knowledge
The AI/ML Catalog, is an organized library for AI/ML workflows such as model training, data transformation, deep learning etc…
Professors can take advantages of the 200 templates already available, change them, adapt them and save them for their purposes.
They can select dedicated folders and share them with specific classes for teaching purposes.
Workflows will access the AI/ML tool used by the teaching staff and connect automatically to the correct part of the IT infrastructure.
A researcher can select ready-made AI/ML workflows and apply them in minutes to their research.
The workflows are open and easily configurable to access data or compute resources on-premises, private or public clouds.
The ActiveEon catalog acts as a central repository of all essential services in automating your AI/ML processes. One crucial part of the process is the possibility of connecting to external data banks such as satellite imagery, social media websites, and others.
Reduce cost & improve services
Better use of
Make cost savings by taking advantage of the compute
power you already have.
For example, make “out of hours” idled or underutilized
computers work for you.
The ActiveEon solution will detect idle computers and,
if allowed, will use them for processing these
hungry AI models training.
You might discover that in fact you do not need to buy
new computers that urgently.
Reduce investment cost by giving professors and researchers the compute power they need. The tasks parallelization of ActiveEon will enable you to use every single core within your IT infrastructure and speed up your hungry AI/ML processes by 4 to 8 times (customers’ feedback). Make your internal customers happy without splashing money on new computers.
Please do not break your budget. The ActiveEon solution will make it easy to use cloud services and will control the use it. Efficiently managing hybrid infrastructure (on-premises and cloud) allows users to be more productive and flexible in their work and study. Of course, better freedom does not preclude control. So, the orchestration solution will ensure that users do not spend more than their budget allocated on cloud services.