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Forward Deployed Engineer: AI + HPC at Cedana | Y Combinator

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Forward Deployed Engineer: AI + HPC at Cedana | Y Combinator

Hacker News·Forward Deployed Engineer: AI + HPC at Cedana | Y Combinator·4 days ago

#ycombinator #cedana #slurm #research #customer #infrastructure

Introducing Cedana The Problem AI and HPC infrastructure suffers from scarcity and high costs, so when failures happen they are costly in terms of time and money. Cluster productivity directly determines research output and revenue.…

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How Slurm Handles Resource Allocation Internally

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How Slurm Handles Resource Allocation Internally

DEV Community·Muhammad Zubair Bin Akbar·19 days ago

#XKHvxcEY

#sbatch #example #fullscreen #slurm #resources #exit

If you work with HPC clusters, chances are you use slurm every day to submit jobs, monitor queues,...

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Achieving Peak System and Workload Efficiency on NVIDIA GB200 NVL72 with Slurm Block Scheduling

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Achieving Peak System and Workload Efficiency on NVIDIA GB200 NVL72 with Slurm Block Scheduling

NVIDIA Technical Blog·Felix Abecassis·25 days ago

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#x5b #datacentercloud #mlops #networkingcommunications #hpcscientificcomputing #slurm

NVIDIA GB200 NVL72 introduces a fundamentally new way to build GPU clusters by extending NVIDIA NVLink coherence across an entire rack.

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Inside Job Logs: What to Look For When Things Break

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Inside Job Logs: What to Look For When Things Break

DEV Community·Muhammad Zubair Bin Akbar·28 days ago

#iZHhVldS

#sbatch #ai #hpc #slurm #fullscreen #exit

When a job fails on an HPC cluster, your first instinct might be to rerun it and hope for a different...

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Running Large-Scale GPU Workloads on Kubernetes with Slurm

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Running Large-Scale GPU Workloads on Kubernetes with Slurm

NVIDIA Technical Blog·Anton Polyakov·about 1 month ago

#BIO78nP9

#x2d #datacentercloud #developertoolstechniques #networkingcommunications #hpcscientificcomputing #slurm

Slurm is an open source cluster management and job scheduling system for Linux. It manages job scheduling for over 65% of TOP500 systems.

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Running AI Workloads on Rack-Scale Supercomputers: From Hardware to Topology-Aware Scheduling

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Running AI Workloads on Rack-Scale Supercomputers: From Hardware to Topology-Aware Scheduling

NVIDIA Technical Blog·Ryan Prout·about 1 month ago

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#x2d #datacentercloud #developertoolstechniques #networkingcommunications #general #nvlink

The NVIDIA GB200 NVL72 and NVIDIA GB300 NVL72 systems, featuring NVIDIA Blackwell architecture, are rack-scale supercomputers. They’re designed with 18 tightly…

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Forward Deployed Engineer: AI + HPC at Cedana | Y Combinator

How Slurm Handles Resource Allocation Internally

Achieving Peak System and Workload Efficiency on NVIDIA GB200 NVL72 with Slurm Block Scheduling

Inside Job Logs: What to Look For When Things Break

Running Large-Scale GPU Workloads on Kubernetes with Slurm

Running AI Workloads on Rack-Scale Supercomputers: From Hardware to Topology-Aware Scheduling