The ultimate GPU server for deep learning
Now available with NVIDIA H100 NVL Tensor Core GPUs
10,000+ research teams trust Lambda
Lambda Scalar powered by NVIDIA H100 NVL GPUs
Lambda Scalar servers come with the new NVIDIA H100 NVL Tensor Core GPUs and deliver unprecedented performance, scalability, and security for every workload. NVIDIA H100 NVL GPUs feature fourth-generation Tensor Cores and the Transformer Engine with FP8 precision, further extending NVIDIA’s market-leading AI leadership with faster training and inference speedup on large language models.
Engineered for your workload
Tell us about your research and we'll design a machine that's perfectly tailored to your needs.
Easily scale from server to cluster
As your team's compute needs grow, Lambda's in-house HPC engineers and AI researchers can help you integrate Scalar and Hyperplane servers into GPU clusters designed for deep learning.
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ComputeScaling to 1000s of GPUs for distributed training or hyperparameter optimization.
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StorageHigh-performance parallel file systems optimized for ML.
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NetworkingCompute and storage fabrics for GPUDirect RDMA and GPUDirect Storage.
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SoftwareFully integrated software stack for MLOps and cluster management.
Service and support by technical experts who specialize in machine learning
Lambda Premium Support includes:
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Up to 5 year extended warranty with advanced parts replacement
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Live technical support from Lambda's team of ML engineers
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Support for ML software included in Lambda Stack: PyTorch®, Tensorflow, CUDA, CuDNN, and NVIDIA Drivers
Plug in. Start training.
Our servers include Lambda Stack, which manages frameworks like PyTorch® and TensorFlow. With Lambda Stack, you can stop worrying about broken GPU drivers and focus on your research.
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Zero configuration requiredAll your favorite frameworks come pre-installed.
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Easily upgrade PyTorch® and TensorFlowWhen a new version is released, just run a simple upgrade command.
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No more broken GPU driversDrivers will "just work" and keep compatible with popular frameworks.
Your servers. Our datacenter.
Lambda Colocation makes it easy to deploy and scale your machine learning infrastructure. We'll manage racking, networking, power, cooling, hardware failures, and physical security. Your servers will run in a Tier 3 data center with state-of-the-art cooling that's designed for GPUs. You'll get remote access to your servers, just like a public cloud.
Explore our research
Multiple Pairwise Ranking Networks for Personalized Video Summarization
We propose a model for personalized video summaries by conditioning the summarization process with predefined categorical labels.
HoloGAN: Unsupervised Learning of 3D Reps. from Natural Images
We propose a novel generative adversarial network (GAN) for the task of unsupervised learning of 3D representations from natural images.
RenderNet: A Deep ConvNet for Differentiable Rendering from 3D Shapes
We present a differentiable rendering convolutional network with a novel projection unit that can render 2D images from 3D shapes.
Adversarial Monte Carlo Denoising with Conditioned Aux. Feature Modulation
We demonstrate that GANs can help denoiser networks produce more realistic high-frequency details and global illumination.
Technical Specifications
Up to 8 dual-slot PCIe GPUs. Options include:
- NVIDIA H100 NVL: 94 GB of HBM3, 14,592 CUDA cores, 456 Tensor Cores, PCIe 5.0 x16
- NVIDIA L40S: 48 GB of GDDR6, 18,176 CUDA cores, 568 Tensor Cores, PCIe 4.0 x16
- NVIDIA RTX 6000 Ada Generation: 48 GB of GDDR6, 18,176 CUDA cores, 568 Tensor Cores, PCIe 4.0 x16
- NVIDIA RTX 5000 Ada Generation: 32 GB of GDDR6, 12,800 CUDA cores, 400 Tensor Cores, PCIe 4.0 x16
- NVIDIA RTX 4500 Ada Generation: 24 GB of GDDR6, 7,680 CUDA cores, 240 Tensor Cores, PCIe 4.0 x16
- NVIDIA RTX 4000 Ada Generation: 16 GB of GDDR6, 6,144 CUDA cores, 192 Tensor Cores, PCIe 4.0 x16
2 AMD EPYC or Intel Xeon Processors
- AMD EPYC 7004 (Genoa) Series Processors with up to 192 cores total
- Intel Xeon 4th Gen (Sapphire Rapids) Scalable Processors with up to 112 cores total
- Up to 8 TB of 4800 MHz DDR5 ECC RAM in 32 DIMM slots
- Up to 491.52 TB of storage via 16 hot-swappable U.2 NVMe SSDs
- Up to 61.44 TB of storage via 8 hot-swappable 2.5" SATA SSDs
Built-in networking:
- 2 RJ45 10 Gbps BASE-T LAN ports
- 1 RJ45 1 Gbps BASE-T LAN out-of-band management port
Optional high-speed NIC. Options include:
- NVIDIA ConnectX-7 400 Gb/s NDR InfiniBand Adapter, OSFP56, PCIe 5.0 x16
- NVIDIA ConnectX-7 200 Gb/s NDR200 InfiniBand Adapter, OSFP56, PCIe 5.0 x16
- NVIDIA ConnectX-7 200 Gb/s NDR200 InfiniBand/VPI Adapter, QSFP112, PCIe 5.0 x16
- NVIDIA ConnectX-6 200 Gb/s HDR InfiniBand/VPI Adapter, QSFP56, PCIe 4.0 x16
- NVIDIA ConnectX-6 100 Gb/s HDR100 InfiniBand/VPI Adapter, 1x QSFP56, PCIe 4.0 x16
- NVIDIA ConnectX-6 Dx EN 200 Gb/s Ethernet Adapter, QSFP56, PCIe 4.0 x16
- NVIDIA ConnectX-6 Dx EN 100 Gb/s Ethernet Adapter, QSFP56, PCIe 4.0 x16
- NVIDIA ConnectX-5 EN 100 Gb/s Ethernet Adapter, QSFP28, PCIe 3.0 x16
- 4 hot-swappable 2000 watt 80 PLUS Titanium PSUs
- 2 + 2 redundancy
- 220-240 Vac / 10-9.8A / 50-60 Hz
- 220-240Vac / 2000 watts
- Power button
- Reset button
- Power LED
- ID button with LED
- Information LED
- Power supply failure LED
- 2 LAN activity LEDs, one for each RJ45 1
- Gbps BASE-T LAN port
Storage drive activity LED
- VGA port
- 2 USB 3.0 ports
- 2 RJ45 10 Gbps BASE-T LAN ports
- 1 RJ45 1 Gbps BASE-T LAN out-of-band management port
- Rackmounting kit
- 4 configurable C19 power cables
- Form factor: 4U rackmount
- Width: 17.2 inches (437 mm)
- Height: 7.0 inches (179 mm)
- Depth: 29.0 inches (737 mm)
- Server weight: 73 lbs (33 kg)
- Rackmounting kit weight: 5 lbs (2.3 kg)
- Total weight with packaging: 99 lbs (45 kg)