NVIDIA CMP 40HX
About GPU
The NVIDIA CMP 40HX GPU is a solid choice for anyone in need of a powerful and efficient mining GPU. With a base clock of 1470MHz and a boost clock of 1650MHz, this GPU is capable of handling even the most demanding mining tasks with ease. The 8GB of GDDR6 memory, with a clock speed of 1750MHz, ensures smooth and efficient performance, even when dealing with large datasets.
The 2304 shading units and 4MB of L2 cache further contribute to the overall performance of the CMP 40HX, allowing for quick and accurate processing of complex algorithms. The 185W TDP is not only manageable but also ensures that the GPU operates efficiently without consuming too much power.
With a theoretical performance of 7.603 TFLOPS, the CMP 40HX is more than capable of handling a wide range of mining workloads, making it a versatile and reliable option for miners of all skill levels. Additionally, its desktop platform makes it easy to integrate into existing mining rigs without any hassle.
Overall, the NVIDIA CMP 40HX GPU is a powerful and efficient solution for anyone in need of a reliable mining GPU. With its impressive specs and solid performance, it is sure to meet the needs of even the most demanding mining operations.
Basic
Label Name
NVIDIA
Platform
Desktop
Launch Date
February 2021
Model Name
CMP 40HX
Generation
Mining GPUs
Base Clock
1470MHz
Boost Clock
1650MHz
Bus Interface
PCIe 3.0 x16
Memory Specifications
Memory Size
8GB
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
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.
448.0 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.
105.6 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.
237.6 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.
15.21 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.
237.6 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.
7.451
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.
36
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.
2304
L1 Cache
64 KB (per SM)
L2 Cache
4MB
TDP
185W
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
7.451
TFLOPS
Blender
Score
1320
Vulkan
Score
60353
OpenCL
Score
97694
Compared to Other GPU
FP32 (float)
/ TFLOPS
Blender
Vulkan
OpenCL