A30 on Massed Compute
Visit Massed ComputeMassed Compute offers the NVIDIA A30 GPU as part of its high-performance VM lineup, tailored for remote workstations and engineering simulations. The A30, built on Ampere architecture with 24GB GDDR6 VRAM, excels in AI inference, training, data analytics, and virtualized graphics workloads, delivering up to 10.3 TFLOPS FP32 performance and efficient Tensor Core acceleration. This combination is noteworthy for Massed Compute's ThinLinc technology, providing low-latency, high-fidelity remote desktop access that rivals local hardware—ideal for interactive ML prototyping, visualization, and simulations. Targeted at ML engineers, data scientists, and simulation specialists who avoid on-premises setups, it emphasizes per-hour billing for flexible, cost-effective scaling. Key value propositions include superior remote UX, enterprise-grade reliability, optimized VM configurations, and focus on workloads demanding seamless GPU access without geographical constraints, making it a strong choice for project-based or remote team collaborations.
Why NVIDIA A30 on Massed Compute?
Opt for Massed Compute's NVIDIA A30 if remote workstation excellence is paramount. Their ThinLinc integration delivers buttery-smooth remote desktop performance, leveraging the A30's versatility for inference-heavy ML tasks, graphics rendering, and simulations far better than standard VNC/RDP on other clouds. Per-hour billing aligns perfectly with sporadic usage patterns common in engineering workflows, minimizing costs versus reserved instances. As a boutique provider, they offer tailored high-performance VMs with likely fast NVMe storage and reliable uptime, complementing the A30's efficiency for mainframe-scale inference and analytics. This setup shines for users prioritizing usability over raw scale, providing a 'local-like' experience without hardware hassles.
Live Pricing
Real-time NVIDIA A30 offers from Massed Compute
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Massed Compute | NVIDIA A30 24GB VRAM | 24GB | 16 vCPU 48GB RAM 256GB Storage | 🌍global | $0.35/GPU/hr | Sold Out | ||
Massed Compute | 2×NVIDIA A30 24GB VRAM | 24GB | 30 vCPU 96GB RAM 512GB Storage | Iowa | $0.35/GPU/hr $0.70/hr total (2×) | Sold Out | ||
Massed Compute | 2×NVIDIA A30 24GB VRAM | 24GB | 30 vCPU 96GB RAM 512GB Storage | 🌍global | $0.35/GPU/hr $0.70/hr total (2×) | Sold Out | ||
Massed Compute | 4×NVIDIA A30 24GB VRAM | 24GB | 50 vCPU 192GB RAM 1024GB Storage | 🌍global | $0.35/GPU/hr $1.40/hr total (4×) | Sold Out | ||
Massed Compute | NVIDIA A30 24GB VRAM | 24GB | 16 vCPU 48GB RAM 256GB Storage | Iowa | $0.35/GPU/hr | Sold Out |
Performance Notes
On Massed Compute, expect the A30 to deliver standard Ampere benchmarks: ~165 TFLOPS FP16 Tensor, strong for inference (e.g., BERT-large at 100+ seq/s) and moderate training. Provider's high-perf VMs suggest ample CPU/RAM pairing (e.g., 16-32 cores, 128GB+), but exact specs vary by config. Network bandwidth likely 10-25 Gbps, suitable for data transfer; storage options include fast SSDs for datasets. Multi-GPU scaling unknown—assume single-GPU focus for workstations, no NVLink details available. ThinLinc enables responsive remote perf, but latency-sensitive tasks may vary by user location. Benchmarks are provider-specific limited; test for your workload as real-world results depend on software stack and optimization.
A boutique provider focusing on high-performance VMs for remote workstations and simulations.
Best For
Unique Features
- ThinLinc technology for superior remote desktop performance
VRAM
24GB
Architecture
Ampere
Tier
enterprise
Platform Features
Getting Started
Launching an NVIDIA A30 instance on Massed Compute is straightforward via their dashboard. Sign up, select the A30 config optimized for remote workstations, launch per-hour, and connect via ThinLinc for low-latency access—perfect for quick ML prototyping or simulations without setup delays.
Steps
- 1Create a free account on the Massed Compute website and add payment details.
- 2Navigate to 'GPU Instances,' select NVIDIA A30, and choose VM size/storage options.
- 3Configure instance (e.g., OS, CUDA version) and set billing duration.
- 4Launch the instance; dashboard provides IP and ThinLinc credentials.
- 5Download ThinLinc client, connect using credentials for remote desktop access.
Pro Tips
- Enable GPU passthrough and hardware acceleration in ThinLinc settings for optimal interactive performance during ML visualization or CAD tasks.
- Pre-load Docker images with CUDA 11.0+ matching A30 drivers to minimize setup time post-launch.
- Track hourly usage via dashboard alerts to pause idle instances and control costs effectively.
Frequently Asked Questions
What is Massed Compute's billing model for NVIDIA A30?▾
Massed Compute bills per-hour for GPU instances including NVIDIA A30. Hourly billing means you pay for full hours even if your job completes mid-hour. Plan your workloads accordingly to maximize cost efficiency.
Does Massed Compute offer spot instances for NVIDIA A30?▾
No, Massed Compute does not currently offer spot instances for NVIDIA A30. All instances are billed at on-demand rates. However, they do offer reserved instances for committed usage, which can provide significant discounts for long-term workloads.
Does Massed Compute offer reserved instances for NVIDIA A30?▾
Yes, Massed Compute offers reserved instance pricing for NVIDIA A30, which can provide significant discounts (typically 20-40% off on-demand rates) for committed usage periods. Reserved instances are ideal for predictable, long-running workloads like production inference services, ongoing training pipelines, or development environments that run continuously. Contact Massed Compute for current reserved pricing and commitment terms.
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