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About

Massed Compute offers high-performance GPU computing solutions tailored for AI, machine learning, scientific simulations, and data analytics. As an NVIDIA Preferred Partner, it provides access to a comprehensive catalog of enterprise-grade NVIDIA GPUs, including A100, H100, L40, and A6000, ensuring optimal performance for various workloads. Users can choose between bare metal servers for maximum control and performance or on-demand compute instances for flexibility and scalability. Massed Compute's Inventory API allows seamless integration of GPU resources into existing business platforms, enabling provisioning, rebooting, and management of instances with ease. Massed Compute's infrastructure is housed in Tier III data centers, offering consistent uptime, advanced redundancy, and efficient cooling systems. With SOC 2 Type II compliance, the platform ensures high standards of security and data protection.

About

NVIDIA Base Command Manager offers fast deployment and end-to-end management for heterogeneous AI and high-performance computing clusters at the edge, in the data center, and in multi- and hybrid-cloud environments. It automates the provisioning and administration of clusters ranging in size from a couple of nodes to hundreds of thousands, supports NVIDIA GPU-accelerated and other systems, and enables orchestration with Kubernetes. The platform integrates with Kubernetes for workload orchestration and offers tools for infrastructure monitoring, workload management, and resource allocation. Base Command Manager is optimized for accelerated computing environments, making it suitable for diverse HPC and AI workloads. It is available with NVIDIA DGX systems and as part of the NVIDIA AI Enterprise software suite. High-performance Linux clusters can be quickly built and managed with NVIDIA Base Command Manager, supporting HPC, machine learning, and analytics applications.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

AI researchers, data scientists, and developers requiring a solution to accelerate machine learning, scientific simulations, and data analytics workloads

Audience

Organizations seeking a tool to manage the deployment of their AI and HPC clusters across diverse computing environments

Support

Phone Support Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

$21.60 per hour
Free Version Not Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 1.0 / 5
ease 1.0 / 5
features 1.0 / 5
design 1.0 / 5
support 1.0 / 5

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Pros & Cons from Real Users

Pros

  • Cheap price. But they get money from you in other ways. To be honest, there really isn't much else positive to talk about from my experience.

Cons

  • frequently unavailable, and when I finally deployed a VM with 4× H200 NVL GPUs on Ubuntu 24.04, the system image contained software packages that were significantly older than the versions that normally come with a standard Ubuntu 24.04 installation. In addition, CUDA was preinstalled, but it was also an outdated version. It gave the impression that an intentionally outdated software environment had been prepared, although I cannot confirm that. As a result, I had to spend a significant amount of billed time updating the system packages, CUDA, drivers, and related dependencies before I could begin my work. More importantly, the GPUs did not appear to have working NVLink connectivity, and CUDA peer-to-peer access between GPUs was unavailable. For multi-GPU workloads, this is a major limitation because GPU-to-GPU communication is critical for performance. I also requested a refund for my remaining unused credits, but it was declined. My interactions with support were slow and unhelpful.

Training

Documentation Supported
Webinars Not Supported
Live Online Supported
In Person Supported

Training

Documentation Supported
Webinars Supported
Live Online Supported
In Person Supported

Company Information

Massed Compute
United States
massedcompute.com

Company Information

NVIDIA
Founded: 1993
United States
www.nvidia.com/en-us/data-center/base-command/manager/

Alternatives

CambridgeNexus

CambridgeNexus

CambridgeNexus, Inc.

Alternatives

Categories

AI Cloud Providers Supported
Bare Metal Server Supported
Cloud GPU Supported
Render Farms Supported

Categories

Cluster Management Supported

Integrations

Kubernetes Not Supported
NVIDIA AI Enterprise Not Supported
NVIDIA Base Command Not Supported
NVIDIA Cumulus Linux Not Supported
NVIDIA DGX Cloud Not Supported
NVIDIA DRIVE Supported
NVIDIA virtual GPU Not Supported
Shadeform Supported

Integrations

Kubernetes Supported
NVIDIA AI Enterprise Supported
NVIDIA Base Command Supported
NVIDIA Cumulus Linux Supported
NVIDIA DGX Cloud Supported
NVIDIA DRIVE Not Supported
NVIDIA virtual GPU Supported
Shadeform Not Supported
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Claim Massed Compute and update features and information
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