NVIDIA Quadro RTX 8000 Passive
About GPU
The NVIDIA Quadro RTX 8000 Passive GPU is a top-of-the-line professional graphics card designed for demanding workloads in fields such as content creation, CAD, scientific visualization, and AI development. With its powerful specs and cutting-edge features, it offers an exceptional level of performance and efficiency.
The GPU boasts a base clock speed of 1230MHz and a boost clock speed of 1620MHz, ensuring smooth and reliable operation even under heavy workloads. Its massive 48GB of GDDR6 memory, combined with a memory clock speed of 1750MHz, allows for seamless handling of large datasets and complex simulations. The 4608 shading units and 6MB of L2 cache further contribute to its impressive performance capabilities.
One of the standout features of the Quadro RTX 8000 is its passive cooling system, which provides efficient heat dissipation without the need for noisy fans. This not only results in quieter operation but also reduces the risk of dust accumulation and potential mechanical failures, making it ideal for use in noise-sensitive environments.
With a TDP of 260W and a theoretical performance of 14.93 TFLOPS, this GPU delivers unparalleled power efficiency and computational horsepower. Its support for real-time ray tracing, AI-based features, and advanced rendering techniques further solidifies its position as a versatile and future-proof solution for professionals in various industries.
In conclusion, the NVIDIA Quadro RTX 8000 Passive GPU is a formidable choice for professionals seeking uncompromising performance, reliability, and flexibility in a graphics card. Its exceptional specs and innovative cooling design make it a worthy investment for high-end workstations and specialized computing tasks.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
August 2018
Model Name
Quadro RTX 8000 Passive
Generation
Quadro
Base Clock
1230MHz
Boost Clock
1620MHz
Bus Interface
PCIe 3.0 x16
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
1750MHz
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.
672.0 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.
155.5 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.
466.6 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.
29.86 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.
466.6 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.
14.631
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.
72
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.
4608
L1 Cache
64 KB (per SM)
L2 Cache
6MB
TDP
260W
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
Benchmarks
FP32 (float)
Score
14.631
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS