Nvidia A30 Tensor Core Cloud GPU, 24 GB - E2E Cloud

Revolutionize your data processing with A30 Cloud GPUs

The NVIDIA A30 Tensor Core GPU, based on Ampere architecture Tensor Core Technology, is a highly versatile compute GPU designed for mainstream enterprise workloads and AI inference. It supports a wide range of math precisions, making it suitable for speeding up every workload.

The A30 Tensor Core GPU is built for AI inference at scale and can rapidly re-train AI models with TF32. It is also capable of accelerating high-performance computing applications using FP64 Tensor Cores.

A30’s compute capabilities offer high value because of the combination of third-generation Tensor Cores and MIG delivering secure quality of service across diverse workloads, all powered by a versatile GPU enabling an elastic data center.

Learn more about NVIDIA A30
NVIDIA A30 Data Sheet

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Specs

A30

5.2TF
Peak FP64
10.3 TF                    
Peak FP64 Tensor Core
10.3 TF
Peak FP32
82 TF | 165 TF
TF32 Tensor Core
24GB HBM2
GPU Memory
933GB/s
GPU Memory Bandwidth
1 optical flow accelerator (OFA)
Media Engines

Product Features

Here are some key features that make the A30 24GB stand out:

Ampere Architecture

The A30 GPU can accommodate acceleration needs of varying sizes, ranging from small tasks to large multi-node workloads. Its versatility allows users to fully utilize each GPU in their data center, using mainstream servers 24/7. With the A30, there's no need to invest in specialized hardware for specific tasks, as it can handle a wide range of workloads efficiently.

High Bandwidth Memory

With up to 24GB of HBM2 memory and a staggering 933GB/s GPU memory bandwidth, NVIDIA A30 GPU is an excellent choice for diverse AI and HPC workloads. Its mainstream server compatibility makes it an efficient and cost-effective solution for data centers.

MIG Technology

Multi-instance GPU technology allows multiple networks to operate simultaneously on a single A30 by partitioning it into as many as four GPU instances, fully isolated at the hardware level with their own high-bandwidth memory, cache, and compute cores. 

Next-Generation NVLink

The latest generation of NVIDIA NVLink in A30, offers significant improvements in throughput performance, delivering up to double the speed compared to the previous iteration. By utilizing an NVLink Bridge, two A30 PCIe GPUs can be interconnected, resulting in a remarkable deep learning performance of 330 TFLOPs.

Linux A30 GPU Dedicated Compute

Plan
OS
GPU Cards
GPU Memory
vCPU
( ≥ 2.9Ghz)
Dedicated Ram
NVMe Disk Space
Hourly Billing
Weekly Billing
Monthly Billing
(Save 39%)
A30
Ubuntu 16 / Ubuntu 18 / Centos 7
1x NVIDIA A30
1 x 24 GB
16 vCPUs
90 GB
640 GB
₹90/hr
₹12000/week
₹40,000/mo
A30
Ubuntu 16 / Ubuntu 18 / Centos 7
1x NVIDIA A30
2 x 24 GB
32 vCPUs
90 GB
640 GB
₹125/hr
₹14500/week
₹50,000/mo
2xA30
Ubuntu 16 / Ubuntu 18 / Centos 7
2x NVIDIA A30
2 x 24 GB
32 vCPUs
180 GB
1280 GB
₹180/hr
₹24000/week
₹80,000/mo
2xA30
Ubuntu 16 / Ubuntu 18 / Centos 7
2 x 24 GB
2 x 24 GB
64 vCPUs
180 GB
1280 GB
₹250/hr
₹29000/week
₹1,00,000/mo
4xA30
Ubuntu 16 / Ubuntu 18 / Centos 7
4 x 24 GB
4 x 24 GB
64 vCPUs
360 GB
2560 GB
₹360/hr
₹48000/week
₹1,60,000/mo

Windows A30 GPU Dedicated Compute

Plan
GPU Cards
GPU Memory
vCPU
( ≥ 2.9Ghz)
Dedicated Ram
NVMe Disk Space
Hourly Billing
Weekly Billing
Monthly Billing
(Save 36%)
A30
1x NVIDIA A30
1 x 24 GB
16 vCPUs
90 GB
640 GB SSD
₹96/hr
NA
₹45,028/mo
2xA30
2x NVIDIA A30
2 x 24 GB
32 vCPUs
180 GB
1280 GB SSD
₹191/hr
NA
₹88,358/mo
4xA30
4x NVIDIA A30
4 x 24 GB
64 vCPUs
360 GB
2560 GB SSD
₹380/hr
NA
₹1,75,019/mo
Note:

Hypervisor Backend Connectivity - 40Gbps over Fiber
Nvidia QvDWS is per user license, for more RDS licenses can contact our sales team for more detail (Sales@e2enetworks.com)
Additional licenses available on-demand, you can contact to our sales team (Sales@e2enetworks.com)

Why Choose NVIDIA A30 GPU?

A30 is an NVIDIA solution that encompasses essential building blocks across hardware, networking, software, libraries, and optimized AI models and applications from NVIDIA GPU Cloud. Several things set it apart. Some of them are:

  • Structural Sparsity: 2X Higher Performance for AI: Modern AI networks have millions of parameters. Not all of these parameters are needed for accurate predictions, and some can be converted to zeros to make the models “sparse” without compromising their accuracy. Tensor Cores in A30 can provide up to two times higher performance for sparse models. While the sparsity feature more readily benefits AI inference, it can also improve the performance of model training.
  • High-Performance Data Analytics: Analyzing and visualizing massive datasets, and transforming them into valuable insights can be difficult. Conventional scale-out solutions often struggle with the complexities of handling datasets spread across multiple servers. To address this issue, accelerated servers with A30 GPUs offer the necessary computational power. These servers are equipped with large HBM2 memory, providing high bandwidth of 933GB/sec, and offer scalability through NVLink technology. With these capabilities, data scientists can effectively tackle their workloads.
  • Flexible Utilization: Tensor Cores and MIG allow A30 to be used for workloads dynamically. It can be used for production inference at peak demand, and part of the GPU can be repurposed to rapidly re-train those very same models during off-peak hours.
  • Secure Workload Partitioning with MIG: The A30 supports Multi-Instance GPU (MIG) technology, allowing secure partitioning of the GPU to allocate resources to multiple researchers. This ensures isolation, data integrity, and maximum GPU utilization, enabling simultaneous access to compute resources with guaranteed Quality of Service (QoS).
  • Deep Learning Inference: A30 leverages incredible features that optimize inference workload. It accelerates a full range of precisions, from FP64 to TF32 and INT4. Supporting up to four MIGs, 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. 

Real-world Applications of A30 Cloud GPU

E2E’s GPU Cloud is suitable for a wide range of uses.

Deep Learning Inference

The NVIDIA A30 is an excellent choice for deep learning inference due to its powerful features and capabilities. Its combination of powerful hardware, specialized features, and optimized software make it an ideal choice for deep learning inference tasks, offering high performance and efficiency for a wide range of applications. Built on Ambere architecture, it has 24 gigabytes of memory and can support NVIDIA's TensorRT software. Additionally, the A30 benefits from NVIDIA's extensive ecosystem, including CUDA, cuDNN, and various deep learning frameworks, ensuring compatibility and ease of integration with existing workflows.

Data Analytics

The A30's powerful GPU architecture and high memory capacity enable it to efficiently process and analyze large datasets commonly encountered in data analytics. With its CUDA parallel processing capabilities, the A30 can accelerate computationally intensive tasks such as data preprocessing, feature extraction, and statistical calculations.

Video Processing and Transcoding

A30's architecture is designed to handle high-performance computing tasks efficiently, making it capable of handling the demanding computational requirements of video processing. It provides substantial processing power and parallel computing capabilities that can be leveraged to accelerate video encoding, decoding, and transcoding tasks.

High-Performance Computing

The NVIDIA A30 is equipped with FP64 NVIDIA Ampere architecture Tensor Cores, marking a significant advancement in high-performance computing (HPC) performance comparable to the groundbreaking introduction of GPUs. It boasts 24 gigabytes (GB) of GPU memory, offering a remarkable bandwidth of 933 gigabytes per second (GB/s), enabling researchers to solve double-precision calculations swiftly. Additionally, HPC applications can harness the capabilities of TF32, enhancing the efficiency of single-precision operations involving dense matrix multiplication and achieving improved throughput.

Scientific Research

Design and implement data-parallel algorithms that scale to hundreds of tightly coupled processing units: molecular modelling, fluid dynamics and others.

Accelerate Machine Learning and Deep Learning Workloads with up to 70% cost-savings.

Benefits

No Hidden Fees

No hidden or additional charges. What you see on pricing charts is what you pay.

NVIDIA Certified CSP Partner

We are NVIDIA Certified Cloud Service provider partner.

No Hidden Fees

We are using NVIDIA certified hardware for GPU accelerated workloads.

Flexible Pricing

We are offering pay as you go model to long tenure plans.

GPU-accelerated 1-click NGC Containers

E2E Cloud GPUs have super simple one click support for NGC containers for deploying NVIDIA certified solutions for AI/ML/NLP/Computer Vision and Data Science workloads.

How E2E GPU Cloud is helping Cloud Quest in their gaming journey

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