Massed Compute Description
Massed Compute provides advanced GPU computing solutions designed specifically for AI, machine learning, scientific simulations, and data analytics needs. As an esteemed NVIDIA Preferred Partner, it offers a wide range of enterprise-grade NVIDIA GPUs, such as the A100, H100, L40, and A6000, to guarantee peak performance across diverse workloads. Clients have the option to select bare metal servers for enhanced control and performance or opt for on-demand compute instances, which provide flexibility and scalability according to their requirements. Additionally, Massed Compute features an Inventory API that facilitates the smooth integration of GPU resources into existing business workflows, simplifying the processes of provisioning, rebooting, and managing instances. The company's infrastructure is located in Tier III data centers, which ensures high availability, robust redundancy measures, and effective cooling systems. Furthermore, with SOC 2 Type II compliance, the platform upholds stringent standards for security and data protection, making it a reliable choice for organizations. In an era where computational power is crucial, Massed Compute stands out as a trusted partner for businesses aiming to harness the full potential of GPU technology.
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Advertised hardware did not match my experience Date: Jul 17 2026
Summary: My overall experience was disappointing. I spent a considerable amount of billed time updating the CUDA environment instead of running my workloads. The lack of GPU peer-to-peer access and apparent absence of NVLink support made the instance unsuitable for the distributed training workload I rented it for. Combined with hardware availability issues, the refusal to refund unused credits, and an unsatisfactory support experience, I would not choose this platform again.
Positive: 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.
Negative: 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 In addition, CUDA was preinstalled, but it was also an outdated version. It gave the impression that an intentionally outdated software environment had been prepared, although I cannot confirm that.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.
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