Professional Multi-GPU Workstations & High-Density Cluster Nodes

High-Performance GPU Systems for CryoSPARC

Purpose-built computational platforms for cryogenic electron microscopy (cryo-EM). Accelerate your single-particle analysis pipelines—from motion correction and 2D classification to sub-angstrom 3D refinement—with our massive multi-GPU architectures.

Motion Correction & PreprocessingUltra-fast NVMe architectures for handling massive streaming multi-frame movie files (e.g., K3/Falcon 4) without I/O bottlenecks
2D Classification & Particle PickingHigh-frequency GPU clusters designed for automated, AI-driven template matching and particle extraction from raw micrographs
High-Resolution 3D RefinementDense VRAM configurations supporting massive particle box sizes to achieve sub-angstrom atomic resolution
CryoSPARC Live ProcessingMulti-GPU workstations optimized for real-time, on-the-fly reconstruction directly synchronized with the microscope’s data collection session

Cryo-EM Software Ecosystem & Deployment Support

Every CryoSPARC workstation ships with OS installed, NVIDIA CUDA toolkits validated, and GPU drivers configured. Our engineers verify solver execution and run benchmark reconstructions before handover.

We Validate Your Cryo-EM Environment

Skip the complex database and CUDA configurations. Kirti Telnet provisions your hardware with validated NVIDIA drivers, MongoDB dependencies, and pre-configured CryoSPARC Master/Worker node setups so you can begin processing micrographs instantly.

Primary Processing Pipeline

End-to-End Single Particle Analysis

Best for: End-to-End Single Particle Analysis

CryoSPARC — GPU-accelerated cryo-EM processing for 2D/3D classification and refinement
CryoSPARC Live — Real-time on-the-fly reconstruction during microscope data collection

Alternative / Secondary Pipelines

Cross-Validation of Atomic Models

Best for: Cross-Validation of Atomic Models

RELION — Bayesian approach to cryo-EM structure determination
cisTEM — User-friendly single-particle image processing suite

Visualization & Modeling

Map Fitting & Atomic Model Building

Best for: Map Fitting & Atomic Model Building

UCSF ChimeraX — Interactive visualization of molecular structures and density maps
Coot — Macromolecular model building into electron density
Phenix — Automated structure refinement and validation

Supported Operating Systems

HPC & Scientific Compliance

Best for: HPC & Scientific Compliance

Ubuntu LTS — Preferred Linux for CUDA development & CryoSPARC deployment
Rocky Linux — Enterprise-grade RHEL-compatible OS for scientific computing

Enterprise System Matrix — CryoSPARC GPU Systems

CryoSPARC relies on a delicate balance of resources. Fast CPUs prepare the data, massive PCIe Gen 5 NVMe arrays stream the multi-terabyte movies, and multiple high-VRAM GPUs execute the 3D reconstruction. Our systems are balanced to ensure no component starves the pipeline.

All prices are tentative and subject to change based on configuration and component availability. CryoSPARC software licenses are procured separately.

Tier 1

Entry Cryo-EM Node

Small-scale single-particle datasets and introductory cryo-EM preprocessing with GPU-accelerated motion correction.

CPU: 1x Intel Core i9-14900K (24C/32T)
RAM: 64 GB DDR5
GPU: 1x NVIDIA RTX 4000 Ada Generation
Storage: 1 TB Gen4 NVMe
~₹2,90,000
Starting Price

Tier 2

Advanced Processing Workstation

Mid-throughput cryo-EM datasets, extended 2D classification runs, and ab-initio 3D reconstruction with ECC-validated memory.

CPU: 1x AMD Ryzen Threadripper 7960X
RAM: 128 GB DDR5 ECC (4-Channel)
GPU: 1x NVIDIA RTX 4500 Ada 24GB
Storage: 2 TB Gen4 NVMe
~₹6,80,000
Starting Price

Tier 3

CryoSPARC Live Station (Dual-GPU)

Real-time on-the-fly reconstruction during microscope sessions, simultaneous preprocessing and 3D refinement with 8-channel ECC memory bandwidth.

CPU: 1x AMD Threadripper PRO 7975WX
RAM: 256 GB DDR5 ECC (8-Channel)
GPU: 2x NVIDIA RTX 5000 Ada 32GB
Storage: 2 TB Gen5 NVMe + 2TB Scratch
~₹14,60,000
Starting Price

Tier 4

Extreme Reconstruction Rig (Quad-GPU)

Massive particle datasets, large box sizes exceeding 700³, and high-resolution sub-angstrom refinement with quad 48GB GPU acceleration.

CPU: 1x AMD Threadripper PRO 7995WX
RAM: 512 GB DDR5 ECC (8-Channel)
GPU: 4x NVIDIA RTX 6000 Ada 48GB
Storage: 4 TB Enterprise NVMe RAID
~₹39,00,000
Starting Price

Tier 5

Enterprise Cryo-EM Cluster Node

Distributed CryoSPARC Master/Worker cluster deployments, enterprise job scheduling, multi-dataset parametric sweeps, and quad-GPU L40S compute for maximum reconstruction throughput.

CPU: Dual AMD EPYC 9004 Series (Up to 128C)
RAM: 1 TB DDR5 ECC Reg (12-Channel)
GPU: 4x NVIDIA L40S 48GB
Storage: 7.68 TB Enterprise U.2 NVMe
~₹43,00,000
Starting Price

Engineering Disclaimer: Optimal reconstruction speed in CryoSPARC scales with GPU VRAM and the number of CUDA cores. Multi-GPU setups require CryoSPARC licensing that supports multi-GPU worker nodes.

Architectural Features & Performance

The Multi-GPU Requirement for CryoSPARC Live

To keep up with modern data collection (generating terabytes of movies per day), a single GPU is rarely enough. We recommend 2 to 4 GPUs per system, allowing you to dedicate GPUs to concurrent tasks: one for preprocessing/motion correction, and others for streaming 2D classification and 3D refinement.

Eliminating the Storage I/O Bottleneck

Cryo-EM generates colossal datasets. Reading massive TIFF/MRC movie files directly dictates pipeline speed. Our workstations utilize PCIe Gen 5 NVMe scratch drives configured in RAID, delivering up to 14,000 MB/s sustained read speeds, ensuring the GPUs are never starved waiting for data to load.

GPU VRAM and Box Sizes

The maximum particle box size you can process is strictly limited by your GPU’s VRAM. While 11GB is the bare minimum for modern data, massive macromolecular complexes require substantial memory. We deploy RTX Ada Generation GPUs with 24GB, 32GB, and 48GB of VRAM to comfortably handle box sizes well over 700³ without crashing.

Frequently Asked Questions

How many GPUs do I need for CryoSPARC?

While CryoSPARC can run on a single GPU, a multi-GPU setup is highly recommended. For CryoSPARC Live, utilizing at least 2 to 4 GPUs allows you to process data synchronously with microscope collection—dedicating GPUs to preprocessing, 2D classification, and 3D refinement simultaneously.

Why is SSD Scratch storage so critical for Cryo-EM?

Preprocessing steps (like motion correction) require fast copies of movie data from the disk to the GPU. Standard hard drives (HDDs) or network-attached storage (NAS) will severely bottleneck this process. An ultra-fast NVMe SSD scratch drive is mandatory for optimal throughput.

Do I need a high-end CPU if the GPU does the heavy lifting?

Yes. CryoSPARC requires a CPU with high memory bandwidth (greater than 100 GB/s) to feed data efficiently to the GPUs. We configure AMD Threadripper PRO and EPYC architectures specifically to maximize this CPU-to-GPU data pipeline.

Does Kirti Telnet provide Master/Worker cluster setups?

Absolutely. For larger core facilities, we can architect a distributed environment with a lightweight Master node (managing the database and web app) orchestrating multiple heavy, multi-GPU Worker nodes for maximum throughput.

Request Custom Cryo-EM Architecture

Talk to KTPL’s infrastructure engineers for a workload assessment and GPU-optimised hardware recommendation for your CryoSPARC cryo-EM environment.

Request Hardware Configuration →

Get in Touch Today for Expert Solutions and Support