-
Duffy returns for New Zealand against West Indies
-
Majestic Olise raises France to another level at World Cup
-
Mbappe dazzles as France march on at World Cup; Norway, Mexico advance
-
Mexico see off Ecuador to break 40-year World Cup curse
-
US govt lifts restrictions on powerful AI models, Anthropic says
-
'My dream is broken': Japan visa rules push out foreign residents
-
Trump earned over $1 bn from crypto ventures in 2025
-
Indian sailors fear returning to Gulf after Middle East war
-
The Afghan women farmers keeping their village alive
-
Fear and anger brew inside Meta amid AI frenzy
-
Asian stocks fluctuate as traders eye crucial US jobs data
-
After 250 years, the 'American dream' is tarnished but alive
-
Madison Square Garden: from Nazis to Knicks, and now... Taylor's wedding?
-
'I'm going to stay calm': 48 hours under the rubble in Venezuela
-
'Love it': Wimbledon's military stewards tradition turns 80
-
Breakaway Catholic sect defies Vatican again by ordaining bishops
-
Venezuela quake survivors cherish kindness of strangers
-
Mexico v Ecuador World Cup game delayed by one hour: FIFA
-
US deports first migrant to Pacific nation Palau
-
Talks in Qatar after US-Iran deal: What we know
-
Potter admits Sweden couldn't live with France in World Cup defeat
-
Tuchel refuses to dampen England World Cup expectations
-
US coach dismisses European jinx ahead of Bosnia clash
-
Mbappe hails unity as France rally around Deschamps at World Cup
-
World Bank to phase out lending to China by 2031
-
Mbappe fires France into World Cup last 16, Norway advance
-
Mbappe scores twice as France breeze past Sweden into World Cup last 16
-
Belgium fully fit ahead of Senegal tie at World Cup, says Garcia
-
No corn dogs? Trump's 'Great American State Fair' threatens to be a flop
-
Tepid outlook weighs on Nike despite tariff refund boost
-
Haaland hailed as 'greatest' after more World Cup heroics
-
DR Congo have 'nothing to lose' in England World Cup clash
-
Koeman steps down as Netherlands coach after World Cup exit
-
Valiant Serena beaten on Wimbledon return, Swiatek survives scare
-
Nasdaq ends best quarter in 6 years as yen extends drop against dollar
-
Serena beaten at Wimbledon in first singles match in four years
-
Zverev says Wimbledon hopes 'about me' despite open draw
-
Dutch football chiefs condemn online racism after World Cup exit
-
Lionel Scaloni: Argentina's mastermind marks 100 games in charge
-
Police hunt for Monaco bomber after Ukraine-born tycoon wounded
-
Mourinho's Real Madrid host Real Sociedad in La Liga opener
-
CIA boss compares cutting-edge AI to nuclear weapons
-
Football brings joy to Venezuelan kids displaced by quakes
-
'Any team can beat you', warns Ruiz as Spain seek end to World Cup woe
-
Haaland fires Norway into last 16 as France, Mexico look to advance
-
Venezuela quake survivors seek food, shelter as toll rises to nearly 2,000
-
Merkel unveils official portrait for German chancellery
-
Haaland scores winner to send Norway into last-16 Brazil clash
-
Canada crews battle northern wildfire after crash kills 3
-
US Treasury sanctions target alleged drug cartel-linked fuel smuggling ring
ClearML Debuts One-Click Solution for Running Slurm Workloads on Kubernetes, Reducing HPC Deployment Overhead
New solution reduces HPC deployment time by 90% while maintaining native Slurm functionality and Kubernetes flexibility and full operational visibility
SAN FRANCISCO, CA / ACCESS Newswire / November 18, 2025 / ClearML, the leading end-to-end solution for GPU management and unleashing AI in the enterprise, today launched one-click dynamic Slurm cluster deployment on Kubernetes infrastructure. The new solution eliminates the operational overhead and inefficiencies maintaining dedicated high-performance computing (HPC) clusters with Kubernetes requirements for AI workloads. With ClearML Slurm deployment, IT admins can deploy dynamically scalable Slurm clusters for HPC workloads with scale-to-zero autoscaling and monitoring capabilities absent from mixed Slurm and Kubernetes environments.
By enabling Slurm scheduling on Kubernetes infrastructure, ClearML allows organizations to effortlessly maintain existing workflows while gaining the benefits and flexibility of secure Kubernetes orchestration. Enterprises benefit from elastic clusters with dynamic resizing, including scale-to-zero when not in use, while GPU passthrough orchestration enables workloads to achieve bare-metal performance, avoiding the need to manage a dedicated Slurm cluster.
This new solution, available within ClearML's Infrastructure Control Plane, provides a dashboard with real-time visibility into job status, execution history, and failure diagnostics while enabling secure multi-tenant deployments with dynamic Slurm clusters and fully secure separation of resources, network and storage for each tenant. This expanded capability for workload management reduces the overhead for IT teams while also providing flexibility for AI builders and traditional HPC workload management.
"HPC teams shouldn't have to choose between the Slurm workflows they trust and the flexibility of cloud-native infrastructure," said Moses Guttmann, CEO & Co-founder of ClearML. "We're eliminating the administrative burden of dedicated Slurm clusters while adding the autoscaling, monitoring, and multi-tenancy capabilities that HPC teams need as their computational demands evolve."
With ClearML, HPC and AI workloads can operate on shared infrastructure unobstructed, addressing the growing need of enterprises and organizations running both traditional HPC workloads such as physics simulations in conjunction with AI workloads.
ClearML also launched one-click deployment of multi-node AI training, simplifying distributed training operations across any hardware infrastructure. This new capability automatically orchestrates codebases based on frameworks such as pytorch distributed and provides a single dashboard into parallelized training workloads including visibility into training progress, the number of running nodes, and their statuses. Organizations can leverage the feature for fine-tuning large language models, training foundation models, and accelerating training cycles through parallel resource allocation. With this new solution, administrators can dynamically configure the resources available to the distributed training workloads which include native autoscalers that spin down idle instances after a set time. ClearML's one-click multi-node training deployment makes it easy to launch distributed training to accelerate model training and fine-tuning.
Experience Live Demos at SC25
Both new solutions will be demonstrated live at the SC25 Conference (Supercomputing 2025) in St. Louis, Missouri, November 17-20. Visit ClearML at booth #3209.
About ClearML
As the leading infrastructure platform for unleashing AI in organizations worldwide, ClearML is used by more than 2,100 customers to manage GPU clusters and optimize utilization, streamline AI/ML workflows, and deploy GenAI models effortlessly. ClearML is an NVIDIA partner and is trusted by more than 300,000 forward-thinking AI builders and IT teams at leading Fortune 500 companies, enterprises, academia, public sector agencies, and innovative start-ups worldwide. To learn more, visit the company's website at https://clear.ml.
Media Contact
Noam Harel
Chief Marketing Officer
ClearML
[email protected]
SOURCE: ClearML, Inc.
View the original press release on ACCESS Newswire
P.A.Mendoza--AT