NVIDIA RTX 4000 SFF Ada Generation

NVIDIA Ada Lovelace Architecture

NVIDIA RTX™ 4000 SFF Ada Generation is the most powerful dual slot, low profile workstation GPU offering high-performance, real-time ray tracing, AI-accelerated compute, and professional graphics rendering, all of this in a compact design with unmatched performance. Building upon the major SM enhancements from the Ada Lovelace GPU, the NVIDIA Ada Lovelace architecture provides more cores, higher clocks, and a larger L2 cache for more performance to enhance ray tracing operations, tensor matrix operations, and frame rates with DLSS 3.0.

NVIDIA CUDA Cores

The NVIDIA Ada Lovelace architecture-based CUDA Cores offer more than 2X the single-precision floating point (FP32) throughput compared to the previous generation, providing significant performance improvements for graphics workflows such as 3D model development and compute for workloads such as desktop simulation for computer-aided engineering (CAE). The RTX 4000 SFF enables two FP32 primary data paths, doubling the peak FP32 operations.

Third-Generation RT Cores

Incorporating 3rd generation ray tracing engines, NVIDIA Ada Lovelace architecture-based GPUs provide incredible ray-traced rendering performance. A single RTX 4000 SFF board can render complex professional models with physically accurate shadows, reflections, and refractions to empower users with instant insight. Working in concert with applications leveraging APIs such as NVIDIA OptiX, Microsoft DXR, and Vulkan ray tracing, systems based on the RTX 4000 SFF will power truly interactive design workflows to provide immediate feedback for unprecedented levels of productivity. The RTX 4000 SFF features up to 2X faster ray-triangle intersection throughput compared to the previous generation.

Fourth-Generation Tensor Cores

Specialized for deep learning matrix multiply and accumulate math operations at the heart of neural network training and inferencing functions, the RTX 4000 SFF includes enhanced Tensor Cores that accelerate more data types and still support the Fine-Grained Structured Sparsity feature that delivers more than 2X throughput for tensor matrix operations compared to the previous generation. New Tensor Cores will accelerate new FP8 precision modes. Independent floating-point and integer data paths allow more efficient execution of workloads using a mix of computation and addressing calculations.

Higher Speed GDDR6 Memory

Built with 20GB GDDR6 memory, the RTX 4000 SFF provides an ideal memory footprint to address datasets and models in latency-sensitive professional applications and at volume.

PCIe Gen 4

The RTX 4000 SFF supports PCI Express Gen 4, which provides double the bandwidth of PCIe Gen 3, improving data-transfer speeds from CPU memory for data-intensive tasks like AI and data science.

Error Correcting Code (ECC) on Graphics Memory

Meet strict data integrity requirements for mission-critical applications with uncompromised computing accuracy and reliability for workstations.

5th Generation NVDEC Engine¹

NVDEC is well suited for transcoding and video playback applications for real-time decoding. The following video codecs are supported for hardware-accelerated decoding: MPEG-2, VC-1, H.264 (AVCHD), H.265 (HEVC), VP8, VP9, and AV1 video formats. Video encoding at 8K/60 will be achievable for professional video editing.

8th Generation NVENC Engine¹

NVENC can take on the most demanding 4K or 8K video encoding tasks to free up the graphics engine and the CPU for other operations. The RTX 4000 SFF provides better encoding quality than software-based x264 encoders. The RTX 4000 SFF incorporates AV1 video encoding which is 40% more efficient than H.264 encoding for 4K HDR video. AV1 will provide better quality at the same bitrate bandwidth.

Graphics Preemption

Pixel-level preemption provides more granular control to better support time-sensitive tasks such as VR motion tracking.

Compute Preemption

Preemption at the instruction level provides finer-grain control over compute tasks to prevent long-running applications from either monopolizing system resources or timing out.

NVIDIA RTX™ Experience⁴

NVIDIA RTX Experience delivers a suite of productivity tools to your desktop workstation, including desktop recording in up to 8K, automatic alerts for the latest NVIDIA RTX Enterprise driver updates, and access gaming features. The application is available for download here.

Software Optimized for AI

Deep learning frameworks such as Caffe2, MXNet, CNTK, TensorFlow, and others deliver dramatically faster training times and higher multi-node training performance. GPU-accelerated libraries such as cuDNN, cuBLAS, and TensorRT delivers higher performance for both deep learning inference and High-Performance Computing (HPC) applications.

NVIDIA CUDA^® Parallel Computing Platform

Natively execute standard programming languages like C/C++ and Fortran, and APIs such as OpenCL, OpenACC, and Direct Compute to accelerate techniques such as ray tracing, video and image processing, and computation fluid dynamics.

Unified Memory

A single, seamless 49-bit virtual address space allows for the transparent migration of data between the full allocation of CPU and GPU memory.

NVIDIA GPUDirect^® for Video

GPUDirect for Video speeds communication between the GPU and video I/O devices by avoiding unnecessary system memory copies and CPU overhead.

NVIDIA Enterprise Management Tools

Maximize system uptime, seamlessly manage wide-scale deployments, and remotely control graphics and display settings for efficient operations.