Performance Highlights
CUDA Cores
|
3804 |
Tensor Cores
|
224 |
Peak FP64
|
5.2 TFLOPS |
Peak FP64 Tensor Core
|
10.3 TFLOPS |
Peak FP32
|
10.3 TFLOPS |
TF32 Tensor Core
|
82 TFLOPS | 165 TFLOPS* |
BFLOAT16 Tensor Core
|
165 TFLOPS | 330 TFLOPS* |
Peak FP16 Tensor Core
|
165 TFLOPS | 330 TFLOPS* |
Peak INT8 Tensor Core
|
330 TOPS | 661 TOPS* |
GPU Memory
|
24 GB HBM2 |
Memory Bandwidth
|
933 GB/s |
Thermal Solutions
|
Passive |
Maximum Power Consumption
|
165 W |
System Interface
|
PCIe Gen 4.0 | 64 GB/s |
Multi-Instance GPU Support
|
Yes |
vGPU Support
|
Yes |
*With sparsity
Deep Learning Training
A30 leverages groundbreaking features to optimize inference workloads. It accelerates a full range of precisions, from FP64 to TF32 and INT4. Supporting up to four MIGs per GPU, A30 lets multiple networks operate simultaneously in secure hardware partitions with guaranteed quality of service (QoS). Structural sparsity support delivers up to 2x more performance on top of A30's other inference performance gains. NVIDIA's market-leading AI performance was demonstrated in MLPerf Inference. Combined with the NVIDIA Triton Inference Server, which easily deploys AI at scale, A30 brings this groundbreaking performance to every enterprise.
Enterprise -Ready Utilization
A30 with MIG maximizes the utilization of GPU accelerated infrastructure. With MIG, an A30 GPU can be partitioned into as many as four independent instances, giving multiple users access to GPU acceleration. MIG works with Kubernetes, containers, and hypervisor-based server virtualization. MIG lets infrastructure managers offer a right-sized GPU with guaranteed QoS for every job, extending the reach of accelerated computing resources to every user.
High Performance Data Analytics
Data scientists need to be able to analyze, visualize, and turn massive datasets into insights. But scale-out solutions are often bogged down by datasets scattered across multiple servers. Accelerated servers with A30 provide the needed compute power – along with large HBM2 memory, 933 GB/s of memory bandwidth, and scalability with NVLink – to tackle these workloads. Combined with NVIDIA InfiniBand, NVIDIA Magnum IO and the RAPIDS site of open-source libraries, including the RAPIDS Accelerator for Apache Spark, the NVIDIA data center platform accelerates these huge workloads at unprecedented levels of performance and efficiency.
vGPU Software Support
- NVIDIA Virtual PC (vPC)
- NVIDIA Virtual Applications (vApps)
- NVIDIA RTX Virtual Workstation (vWS)
- NVIDIA Virtual Compute Server (vCS)
- vGPU Profiles from 1 GB to 24 GB
Warranty
Free dedicated phone and email technical support
(1-800-230-0130)
Dedicated NVIDIA professional products field application engineers
Resources
Contact gopny@pny.com for additional information.