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NVIDIA A40 PCIe

NVIDIA A40 PCIe: Power for Professionals and High-Tech Enthusiasts

Introduction

The NVIDIA A40 PCIe graphics card, introduced in 2020, remains in demand in 2025 due to its versatility. It combines professional visualization, computing, and artificial intelligence capabilities while maintaining compatibility with modern standards. Let’s explore why this model is relevant five years after its release and who it suits.

Architecture and Key Features

Ampere: The Foundation of Performance

The NVIDIA A40 is built on the Ampere architecture (GA102 GPU), which utilizes a 8-nanometer manufacturing process from Samsung. This architecture provides high transistor density and energy efficiency. Key components:

- CUDA Cores: 10,752 (20% more than the previous Turing generation).

- RT Cores: 84 for hardware-accelerated ray tracing.

- Tensor Cores: 336 for AI tasks and DLSS.

Unique Features

- RTX and DLSS 3.0: Support for improved image scaling and reconstruction.

- NVLink: Allows the combination of two cards for collaborative work (up to 96 GB of combined memory).

- VR Ready: Optimized for virtual reality headsets.

- ECC Memory: Error correction for reliability in critical tasks.

Memory: Speed and Reliability

GDDR6 with ECC: 48 GB for Complex Tasks

The A40 is equipped with 48 GB of GDDR6 memory with ECC support, which is critical for scientific calculations and rendering. Specifications:

- Bus Width: 384-bit.

- Bandwidth: 696 GB/s (14.5 Gbps per module).

- Performance Impact: Large capacity allows working with 8K textures, neural networks, and multi-frame rendering without data loading delays.

Example: In Autodesk Maya, rendering a scene with 50 million polygons is accelerated by 30% compared to the RTX 6000 (24 GB).

Gaming Performance: Not the Main Focus, but Possible

The A40 is positioned as a professional card, but it does support gaming. However, Studio Drivers are optimized for applications, not gaming projects. FPS examples (Ultra settings, without DLSS):

- Cyberpunk 2077 (4K): 45–50 FPS (with RTX Ultra — 28–32 FPS, DLSS 3.0 boosts to 55–60 FPS).

- Microsoft Flight Simulator (1440p): 60–65 FPS.

- Call of Duty: Modern Warfare V (1080p): 120–130 FPS.

Conclusion: For gaming, it's better to choose the GeForce RTX 4090, but the A40 can handle 4K if DLSS is activated.

Professional Tasks: Where the A40 Shines

3D Rendering and Modeling

- Blender: Renders a BMW scene in 1.2 minutes (compared to 2.5 minutes on RTX 3090).

- SolidWorks: Supports RealView with smooth rotation of complex assemblies.

Video Editing

- DaVinci Resolve: 8K projects are edited without proxy files.

- Adobe Premiere Pro: Exports a 1-hour 4K video in 8 minutes (using GPU acceleration).

Scientific Calculations

- CUDA and OpenCL: Accelerates simulations in MATLAB, ANSYS.

- AI/ML: Training models on PyTorch is 1.5 times faster than on the A100 (thanks to driver optimizations).

Power Consumption and Thermal Output

TDP and Cooling

- TDP: 300 W.

- Recommendations: Active cooling system (e.g., turbine solution from PNY) or server chassis with front fans.

- Temperatures: Up to 75°C under load, but for prolonged tasks, it’s better to use a Top-to-Bottom ventilated case.

Compatibility with Cases

- Dimensions: 267 × 111 mm (2 slots). Fits most full-tower and workstation cases.

Comparison with Competitors

AMD Radeon Pro W7800 (32 GB)

- Pros: Cheaper (~$2500), better performance in OpenCL.

- Cons: No ECC, poorer support for AI frameworks.

NVIDIA RTX 6000 Ada (48 GB)

- Pros: Ada Lovelace architecture, 25% faster rendering.

- Cons: Price starting from $7000.

Conclusion: The A40 remains a "sweet spot" in terms of price/performance ratio.

Practical Tips

Power Supply and Platform

- PSU: At least 750 W (80+ Platinum recommended).

- Platform: PCIe 4.0 x16, compatible with Intel Xeon W-3400 and AMD Ryzen Threadripper Pro.

Drivers

- Use Studio Drivers for stability. Game Ready Drivers may cause conflicts in professional applications.

Pros and Cons

Pros:

- 48 GB of ECC memory for heavy workloads.

- Support for NVLink and PCIe 4.0.

- Optimized for professional software.

Cons:

- Price: starting from $3500 (new models).

- Limited availability for retail buyers.

- High power consumption.

Final Conclusion: Who is the A40 For?

- Professionals: Video editors, 3D artists, engineers.

- Research Laboratories: For calculations and neural network training.

- VR/AR Enthusiasts: Power for content creation.

Why A40? It offers a unique balance between reliability, memory capacity, and support for modern technologies, remaining relevant even in 2025. If your budget exceeds $3000 and you need a card for "years to come," this is an optimal choice.

Basic

Label Name

NVIDIA

Platform

Desktop

Launch Date

October 2020

Model Name

A40 PCIe

Generation

Tesla

Base Clock

1305MHz

Boost Clock

1740MHz

Bus Interface

PCIe 4.0 x16

Transistors

28,300 million

RT Cores

Tensor Cores

Tensor Cores are specialized processing units designed specifically for deep learning, providing higher training and inference performance compared to FP32 training. They enable rapid computations in areas such as computer vision, natural language processing, speech recognition, text-to-speech conversion, and personalized recommendations. The two most notable applications of Tensor Cores are DLSS (Deep Learning Super Sampling) and AI Denoiser for noise reduction.

336

TMUs

Texture Mapping Units (TMUs) serve as components of the GPU, which are capable of rotating, scaling, and distorting binary images, and then placing them as textures onto any plane of a given 3D model. This process is called texture mapping.

336

Foundry

Samsung

Process Size

8 nm

Architecture

Ampere

Memory Specifications

Memory Size

48GB

Memory Type

GDDR6

Memory Bus

The memory bus width refers to the number of bits of data that the video memory can transfer within a single clock cycle. The larger the bus width, the greater the amount of data that can be transmitted instantaneously, making it one of the crucial parameters of video memory. The memory bandwidth is calculated as: Memory Bandwidth = Memory Frequency x Memory Bus Width / 8. Therefore, when the memory frequencies are similar, the memory bus width will determine the size of the memory bandwidth.

384bit

Memory Clock

1812MHz

Bandwidth

Memory bandwidth refers to the data transfer rate between the graphics chip and the video memory. It is measured in bytes per second, and the formula to calculate it is: memory bandwidth = working frequency × memory bus width / 8 bits.

695.8 GB/s

Theoretical Performance

Pixel Rate

Pixel fill rate refers to the number of pixels a graphics processing unit (GPU) can render per second, measured in MPixels/s (million pixels per second) or GPixels/s (billion pixels per second). It is the most commonly used metric to evaluate the pixel processing performance of a graphics card.

194.9 GPixel/s

Texture Rate

Texture fill rate refers to the number of texture map elements (texels) that a GPU can map to pixels in a single second.

584.6 GTexel/s

FP16 (half)

An important metric for measuring GPU performance is floating-point computing capability. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy.

37.42 TFLOPS

FP64 (double)

An important metric for measuring GPU performance is floating-point computing capability. Double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy, while single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.

584.6 GFLOPS

FP32 (float)

An important metric for measuring GPU performance is floating-point computing capability. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.

36.672 TFLOPS

Miscellaneous

SM Count

Multiple Streaming Processors (SPs), along with other resources, form a Streaming Multiprocessor (SM), which is also referred to as a GPU's major core. These additional resources include components such as warp schedulers, registers, and shared memory. The SM can be considered the heart of the GPU, similar to a CPU core, with registers and shared memory being scarce resources within the SM.

Shading Units

The most fundamental processing unit is the Streaming Processor (SP), where specific instructions and tasks are executed. GPUs perform parallel computing, which means multiple SPs work simultaneously to process tasks.

10752

L1 Cache

128 KB (per SM)

L2 Cache

6MB

TDP

300W

Vulkan Version

Vulkan is a cross-platform graphics and compute API by Khronos Group, offering high performance and low CPU overhead. It lets developers control the GPU directly, reduces rendering overhead, and supports multi-threading and multi-core processors.

1.3

OpenCL Version

3.0

OpenGL

4.6

DirectX

12 Ultimate (12_2)

CUDA

8.6

Power Connectors

8-pin EPS

Shader Model

6.6

ROPs

The Raster Operations Pipeline (ROPs) is primarily responsible for handling lighting and reflection calculations in games, as well as managing effects like anti-aliasing (AA), high resolution, smoke, and fire. The more demanding the anti-aliasing and lighting effects in a game, the higher the performance requirements for the ROPs; otherwise, it may result in a sharp drop in frame rate.

112

Suggested PSU

700W

Benchmarks

FP32 (float)

Score

36.672 TFLOPS

Blender

Score

5010

Compared to Other GPU

FP32 (float) / TFLOPS

RTX PRO 4000 Blackwell

45.962 +25.3%

RTX 5000 Embedded Ada Generation

41.973 +14.5%

A40 PCIe

36.672

GeForce RTX 5070 Ti Mobile

32.905 -10.3%

A10 PCIe

30.615 -16.5%

Blender

GeForce RTX 5090

15026.3 +199.9%

A40 PCIe

5010

GeForce RTX 2070

2020.49 -59.7%

Radeon RX 6800S

1064 -78.8%

GeForce GTX 980 Ti

552 -89%