NVIDIA RTX 6000 Ada Generation

NVIDIA RTX 6000 Ada Generation

About GPU

The NVIDIA RTX 6000 Ada Generation GPU is an absolute powerhouse in terms of performance and capabilities. With a massive 48GB of GDDR6 memory, a base clock of 915MHz, and a boost clock of 2505MHz, this GPU is designed for intensive tasks and applications, such as AI, deep learning, and professional graphics rendering. One of the standout features of the RTX 6000 is its impressive 18176 shading units, which allow for incredibly detailed and realistic graphics rendering. The 96MB L2 cache also contributes to the GPU's ability to handle massive workloads with ease. In terms of power consumption, the RTX 6000 has a TDP of 300W, which is fairly in line with other GPUs in its class. However, the theoretical performance of 91.06 TFLOPS is where this GPU truly shines. It can handle complex calculations and data processing with incredible speed and efficiency. The RTX 6000 is designed for professionals who require top-of-the-line performance for their work. Whether you're a content creator, AI researcher, or data scientist, this GPU can handle anything you throw at it. The only potential downside is the high price tag, but for those who need the best performance, the investment is well worth it. Overall, the NVIDIA RTX 6000 Ada Generation GPU is a powerhouse in every sense of the word. Its massive memory, high clock speeds, and impressive shading units make it a top choice for professionals in need of exceptional performance.

Basic

Label Name
NVIDIA
Platform
Desktop
Launch Date
December 2022
Model Name
RTX 6000 Ada Generation
Generation
Quadro Ada
Base Clock
915MHz
Boost Clock
2505MHz
Bus Interface
PCIe 4.0 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
2500MHz
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.
960.0 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.
481.0 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.
1423 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.
91.06 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.
1423 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.
89.239 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.
142
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.
18176
L1 Cache
128 KB (per SM)
L2 Cache
96MB
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

Benchmarks

FP32 (float)
Score
89.239 TFLOPS
3DMark Time Spy
Score
10122
Blender
Score
11924
OctaneBench
Score
1114
Vulkan
Score
249714
OpenCL
Score
274348

Compared to Other GPU

FP32 (float) / TFLOPS
166.668 +86.8%
91.042 +2%
62.546 -29.9%
51.381 -42.4%
3DMark Time Spy
20021 +97.8%
12960 +28%
5781 -42.9%
Blender
12832 +7.6%
1222 -89.8%
521 -95.6%
203 -98.3%
OctaneBench
1328 +19.2%
163 -85.4%
89 -92%
47 -95.8%
Vulkan
254749 +2%
83205 -66.7%
54373 -78.2%
30994 -87.6%
OpenCL
362331 +32.1%
91174 -66.8%
66179 -75.9%
45244 -83.5%