NVIDIA RTX 5000 Mobile Ada Embedded
The NVIDIA RTX 5000 Mobile Ada Embedded GPU is an impressive piece of hardware, designed to deliver exceptional performance in a wide range of applications. With a base clock speed of 1425MHz and a boost clock speed of 2115MHz, this GPU is capable of handling the most demanding tasks with ease. The inclusion of 16GB of GDDR6 memory, clocked at 2250MHz, ensures that the GPU can handle large datasets and complex calculations without breaking a sweat.
The RTX 5000 also boasts an impressive 9728 shading units and 64MB of L2 cache, further enhancing its capabilities in rendering complex graphics and processing large amounts of data. With a TDP of 120W, the GPU strikes a good balance between performance and power consumption, making it suitable for use in a range of mobile devices.
In terms of performance, the RTX 5000 delivers a theoretical performance of 41.15 TFLOPS, making it one of the most powerful mobile GPUs on the market. This level of performance makes it well-suited for tasks such as machine learning, data analytics, and 3D rendering, where quick and accurate processing is essential.
Overall, the NVIDIA RTX 5000 Mobile Ada Embedded GPU is a powerful and versatile piece of hardware, well-suited for a wide range of professional applications. Whether you're a data scientist, graphic designer, or content creator, this GPU has the power and features to meet your needs.
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Basic
Label Name
NVIDIA
Platform
Mobile
Launch Date
March 2023
Model Name
RTX 5000 Mobile Ada Embedded
Generation
Quadro Ada-M
Base Clock
1425MHz
Boost Clock
2115MHz
Bus Interface
PCIe 4.0 x16
Transistors
45,900 million
RT Cores
76
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.
304
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.
304
Foundry
TSMC
Process Size
5 nm
Architecture
Ada Lovelace
Memory Specifications
Memory Size
16GB
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.
256bit
Memory Clock
2250MHz
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.
576.0 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.
236.9 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.
643.0 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.
41.15 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.
643.0 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.
40.327
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.
76
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.
9728
L1 Cache
128 KB (per SM)
L2 Cache
64MB
TDP
120W
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
8.9
Power Connectors
None
Shader Model
6.7
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
Benchmarks
FP32 (float)
Score
40.327
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS