The NVIDIA A30 Tensor Core GPU is a versatile, enterprise-grade accelerator designed to deliver powerful performance for AI inference, training, and high-performance computing (HPC)—all within an efficient 165W power envelope. Engineered on the Ampere architecture, the A30 strikes the perfect balance between compute power and energy efficiency, making it ideal for data centers, research institutions, and enterprise deployments.
With 24GB of high-bandwidth memory, multi-instance GPU (MIG) capabilities, and third-generation Tensor Cores, the A30 supports a wide range of compute-intensive applications, from deep learning inference to scientific simulations—all with exceptional cost-efficiency and scalability.
Key Features:
- NVIDIA Ampere Architecture
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- Built with cutting-edge Ampere architecture, enabling accelerated computing across AI, data analytics, and HPC workloads.
- 24GB High-Bandwidth HBM2 Memory
- Large Model Support: Easily handles moderate-sized AI and ML models.
- High Memory Bandwidth: Ensures faster data access for inference and simulation workflows.
- Third-Generation Tensor Cores
- Optimized for deep learning with mixed-precision support (FP16, BF16, INT8, TF32), accelerating inference for models like BERT, ResNet, and vision transformers.
- Multi-Instance GPU (MIG)
- Enables secure partitioning of the GPU into multiple instances, allowing simultaneous execution of multiple workloads on a single A30 card—ideal for shared environments.
Applications:
- Artificial Intelligence & Machine Learning
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- Efficient inference and fine-tuning of language, vision, and recommendation models.
- Scalable AI services using MIG for multi-tenant environments.
- Prototyping and experimentation in AI research labs.
- High-Performance Computing (HPC)
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- Accelerated simulations in molecular dynamics, weather prediction, and engineering.
- Cost-effective compute node option for dense HPC clusters.
- Parallel workloads in scientific and industrial applications.
- Data Center & Enterprise Workloads
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- AI-as-a-service and multi-user GPU platforms.
- Integration with NVIDIA AI Enterprise software stack for seamless deployment.
- Virtualized environments and containerized workflows (support for NVIDIA vGPU, Kubernetes, etc.).
Why Choose NVIDIA A30 Tensor Core GPU?
- Enterprise-Class Efficiency
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- Delivers exceptional performance-per-watt at just 165W TDP—perfect for power-constrained environments.
- Memory Optimized for AI & HPC
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- 24GB of HBM2 memory offers ample space and speed for modern data-centric workloads.
- Advanced AI Acceleration
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- Leverages third-gen Tensor Cores to drive high-throughput, low-latency AI workloads across industries.