NVIDIA L40S GPU
Low cost inference
Last updated
Copyright Continuum Labs - 2023
Low cost inference
Last updated
The NVIDIA L40S GPU was launched late 2022. It is a powerful and versatile compute accelerator designed to meet the growing demands of AI, machine learning, and graphics-intensive applications in the data centre.
As the world becomes increasingly data-driven and AI-powered, there is a pressing need for high-performance computing solutions that can handle complex workloads efficiently and cost-effectively.
NVIDIA has developed the L40S to address this need, providing a solution that balances performance, flexibility, and scalability.
The GPU costs about $US12,000
The L40S is built on the NVIDIA Ada Lovelace architecture, which brings significant improvements in performance and efficiency compared to previous generations.
It is equipped with advanced features such as fourth-generation Tensor Cores, third-generation RT Cores, and the Transformer Engine, making it well-suited for a wide range of applications, including generative AI, large language model inference, 3D graphics, and video processing.
With its high-bandwidth memory, fast data transfer capabilities, and support for the latest display technologies, the L40S is a compelling choice for data centres looking to accelerate their AI and graphics workloads.
TFLOPS stands for "Tera Floating Point Operations Per Second." It's a measure of a computer's performance, specifically in tasks that require many mathematical calculations.
The L40S GPU can perform 1,466 trillion floating-point operations per second when working with tensors, which are multi-dimensional arrays used in machine learning and AI.
RT Cores are specialised processors within the GPU designed to handle ray tracing, a technique used to create realistic lighting and shadows in computer graphics. The L40S GPU can perform 212 trillion floating-point operations per second when using its RT Cores.
Single-precision refers to a specific format for representing decimal numbers in computer memory. The L40S GPU can perform 91.6 trillion floating-point operations per second when working with single-precision numbers.
Tensor Cores are specialised processors designed to accelerate AI and machine learning tasks.
The fourth-generation Tensor Cores in the L40S GPU have hardware support for features like structural sparsity and optimised TF32 format, which help improve performance and efficiency in AI and data science workloads.
The third-generation RT Cores in the L40S GPU have improved capabilities compared to previous generations. They can handle ray tracing more efficiently, resulting in faster and more realistic rendering for applications like product design and architecture.
CUDA (Compute Unified Device Architecture) Cores are the main processing units within the GPU. They are responsible for executing general-purpose computations and are particularly well-suited for tasks that can be parallelized, such as 3D modeling and computer simulations.
The Transformer Engine is a technology in the L40S GPU that optimises the performance and memory usage of transformer-based neural networks, which are commonly used in natural language processing and other AI applications.
It automatically adjusts the precision of calculations to deliver faster results and more efficient use of memory.
DLSS 3
DLSS (Deep Learning Super Sampling) is an AI-based technology that improves the performance and visual quality of rendered images.
DLSS 3, supported by the L40S GPU, uses deep learning and hardware innovations to generate new frames, resulting in smoother and faster rendering with improved latency.
The NVIDIA L40S GPU comes with 48GB of GDDR6 memory, which is a high-bandwidth memory solution designed for graphics-intensive applications.
This large amount of memory allows the GPU to handle complex AI models, large datasets, and high-resolution graphics without running into memory limitations.
The L40S also supports ECC (Error Correction Code), a feature that detects and corrects errors in the memory automatically.
ECC is crucial in mission-critical applications where data integrity is paramount, such as scientific simulations, financial analysis, and healthcare.
By ensuring that the data stored in the GPU memory remains accurate and uncorrupted, ECC helps maintain the reliability and stability of the system.
The memory bandwidth of 864 GB/s refers to the rate at which data can be read from or written to the GPU memory.
A higher memory bandwidth allows the GPU to access and process data more quickly, which is essential when dealing with large datasets or complex models. The L40S's high memory bandwidth enables it to efficiently handle demanding workloads, reducing the time required for data transfer and computation.
The Transformer Engine is a key feature of the L40S GPU that significantly enhances its performance in AI workloads, particularly those involving transformer-based neural networks.
Transformers have become the dominant architecture in natural language processing (NLP) and have found applications in various other domains, such as computer vision and speech recognition.
The Transformer Engine optimises the execution of transformer models by scanning the layers of the neural network and dynamically adjusting the precision of the computations.
It can automatically switch between FP8 (8-bit floating-point) and FP16 (16-bit floating-point) precisions based on the requirements of each layer.
This dynamic precision adjustment allows the GPU to perform computations more efficiently, reducing memory usage and accelerating both training and inference workflows.
By leveraging lower-precision arithmetic (FP8) where possible and using higher precision (FP16) when needed, the Transformer Engine strikes a balance between accuracy and performance.
This optimisation is particularly beneficial for inference tasks, where the L40S can process transformer models with high throughput and low latency, enabling real-time applications such as language translation, text generation, and sentiment analysis.
PCIe (Peripheral Component Interconnect Express) is a high-speed serial interface that connects the GPU to the host system.
The L40S supports PCIe Gen4, which is the latest generation of the PCIe standard, providing a data transfer rate of up to 64 GB/s in each direction (bidirectional).
This high-bandwidth connection allows for fast communication between the GPU and the CPU, as well as other system components, enabling efficient data transfer and minimising bottlenecks.
In addition to the PCIe interface, the L40S also features four DisplayPort 1.4a outputs.
DisplayPort is a digital display interface standard that supports high resolutions and refresh rates.
With four DisplayPort outputs, the L40S can drive multiple high-resolution displays simultaneously, making it suitable for applications that require multi-monitor setups, such as visualisation, data analysis, and content creation.
The dual-slot form factor of the L40S refers to its physical size and the number of expansion slots it occupies in a server chassis.
The dimensions of 4.4" (height) x 10.5" (length) make it compatible with standard server racks and chassis designs.
The maximum power consumption of 350W indicates the peak power draw of the GPU under full load, and the 16-pin power connector ensures that the GPU receives sufficient power to operate at its maximum performance level.
The L40S is built for 24/7 enterprise data centre operations and is designed, built, tested, and supported by NVIDIA to ensure maximum performance, durability, and uptime.
It meets the latest data centre standards and is NEBS (Network Equipment-Building System) Level 3 ready, ensuring reliable operation in demanding environments.
The GPU also features secure boot with root of trust technology, providing an additional layer of security for data centres.
It supports NVIDIA virtual GPU (vGPU) software, allowing multiple virtual machines to share the GPU resources and enabling efficient utilisation in virtualised environments.
The L40S can be deployed in creative industries, such as advertising agencies, game development studios, and movie production houses, to accelerate generative AI tasks.
For example, an advertising agency can use the L40S to generate multiple variations of ad designs, slogans, or product descriptions based on input prompts, allowing them to explore a wide range of creative options quickly.
Similarly, game developers can leverage the L40S to generate realistic textures, 3D models, or even entire game levels procedurally, saving time and effort in the design process.
The L40S can be used to deploy large language models for real-time inference in customer service applications.
For instance, a company can train a language model on their product documentation, FAQs, and customer interaction history, and then use the L40S to power a conversational AI chatbot.
The chatbot can understand and respond to customer queries in natural language, providing instant support and reducing the workload on human customer service representatives. The high-performance Tensor cores and Transformer Engine of the L40S ensure fast and accurate responses, enhancing the customer experience.
Organisations can use the L40S to fine-tune pre-trained large language models for specific domains or use cases.
For example, a healthcare provider can fine-tune an LLM on medical literature, patient records, and clinical guidelines to create a specialised model that can assist doctors in diagnosis, treatment planning, and patient communication.
The computational power of the L40S allows for efficient fine-tuning, even with limited amounts of domain-specific data, enabling organizations to adapt LLMs to their unique requirements.
The L40S can be deployed in design and engineering firms to accelerate collaborative 3D design workflows using NVIDIA Omniverse Enterprise.
Omniverse is a platform that enables real-time collaboration and simulation of 3D models across different software tools and geographic locations.
With the L40S, designers and engineers can work together seamlessly, iterating on complex 3D models, running simulations, and visualising designs in high fidelity.
The GPU's RT cores and CUDA cores provide the necessary performance to render realistic lighting, shadows, and materials in real-time, facilitating faster decision-making and improved design outcomes.
The L40S can be utilised by video streaming platforms and content delivery networks to encode, transcode, and deliver high-quality video content to users.
With support for advanced video codecs like AV1, the L40S can efficiently compress video streams while maintaining high visual quality, reducing bandwidth requirements and improving the user experience.
The GPU's encoding and decoding capabilities enable real-time video processing, allowing for live streaming, on-demand video delivery, and interactive video applications.
Content providers can leverage the L40S to scale their video infrastructure, handling multiple concurrent streams and delivering seamless video playback to a large user base.
In terms of performance metrics, the L40S demonstrates impressive results in various benchmarks.
For example, in the Stable Diffusion image generation benchmark, the L40S can generate 82 images per minute at 512x512 resolution and 17 images per minute at 1024x1024 resolution.
In the Large Language Model inference benchmark, the L40S achieves a 1st token latency of 77ms for the Llama 2-7B model, 143ms for the Llama 2-13B model, and 669ms for the Llama 2-70B model, demonstrating its ability to handle complex language models efficiently.
The NVIDIA L40S GPU is a powerful and versatile solution for data centres seeking to accelerate their AI, machine learning, and graphics workloads.
With its advanced architecture, high-performance components, and support for the latest technologies, the L40S is well-positioned to meet the growing demands of these applications. Its ability to efficiently handle diverse workloads, from generative AI and large language model inference to 3D graphics and video processing, makes it a valuable asset for organizations across various industries.
As the world continues to embrace AI and data-driven solutions, the L40S GPU will play a role in enabling businesses to unlock the full potential of these technologies and stay competitive in the evolving landscape.
Specification
Details
Explanation
Data Centre Ready
Yes, with NEBS Level 3 readiness and secure boot with root of trust
The L40S GPU is designed for continuous (24/7) operations in enterprise data centres. It adheres to high standards including NEBS Level 3 for reliability and includes security features like secure boot and root of trust to protect data integrity.
GPU Architecture
NVIDIA Ada Lovelace Architecture
Uses the latest NVIDIA GPU architecture, providing advanced processing power and efficiency for complex computations.
GPU Memory
48GB GDDR6 with ECC
Offers a large and fast memory capacity with error-correcting code (ECC) to detect and correct data corruption, ensuring data reliability in critical applications.
Memory Bandwidth
864GB/s
The rate at which data can be read from or stored into the GPU memory, indicating high data throughput capabilities.
Interconnect Interface
PCIe Gen4 x16: 64GB/s bidirectional
The bandwidth and type of interface used for connecting the GPU to the motherboard, allowing high-speed data transfer.
CUDA® Cores
18,176
The number of CUDA cores indicates the parallel processing power of the GPU, essential for handling multiple operations simultaneously.
RT Cores / Tensor Cores
142 Third-Generation RT Cores / 568 Fourth-Generation Tensor Cores
RT cores are specialized for ray tracing operations, enhancing realistic lighting and shadows in 3D environments. Tensor cores are designed for deep learning operations, speeding up AI computations.
Core Performance
Various TFLOPS and TOPS metrics
Measures the floating point (TFLOPS) and tensor operations per second (TOPS) performance, key indicators of the GPU’s capability in handling different types of computational loads from graphics rendering to AI processing.
Form Factor
4.4" (H) x 10.5" (L), dual slot
Physical dimensions and slot requirement for the GPU, indicating the amount of space needed within the computer chassis.
Display Ports
4x DisplayPort 1.4a
Type and number of available ports for connecting displays, supporting high-resolution and multiple monitor setups.
Max Power Consumption
350W
The maximum amount of power the GPU consumes, important for understanding the energy requirements and thermal design considerations.
Power Connector
16-pin
The type of power connector used, indicating compatibility with power supplies and the required power delivery for stable operation.
Thermal
Passive
The cooling method used by the GPU, with passive cooling typically involving no fans, relying instead on heat sinks to dissipate heat, useful in environments where noise reduction is critical.
Virtual GPU (vGPU) Software Support
Yes
Indicates support for virtualization, allowing the GPU’s resources to be divided for use by multiple virtual machines, enhancing flexibility in multi-user environments.
vGPU Profiles Supported
Refer to the virtual GPU licensing guide
Details which specific virtual GPU configurations are available and supported, important for setup and management in virtualized environments.
NVENC / NVDEC
3x l 3x (includes AV1 encode and decode)
Specifies the capabilities of NVIDIA's hardware-accelerated video encoding (NVENC) and decoding (NVDEC) including support for the latest AV1 codec, enhancing video processing tasks.
Secure Boot With Root of Trust
Yes
Confirms the presence of mechanisms that verify the integrity of the hardware and software, preventing unauthorized changes to the system.
NEBS Ready Level 3
Yes
Indicates compliance with stringent standards for reliability and robustness required for operation in demanding environments, such as telecommunications facilities.
MIG Support
No
Machine Instance GPU (MIG) support status, which if supported, would allow the physical GPU to be partitioned into smaller instances, each capable of running isolated workloads.
NVIDIA® NVLink® Support
No
Indicates whether the GPU can be connected to other GPUs using NVIDIA’s NVLink technology, which would enable high-speed data sharing enhancing performance in multi-GPU configurations.
