NVIDIA CMP 170HX

NVIDIA CMP 170HX

About GPU

The NVIDIA CMP 170HX GPU is a powerful graphics processing unit designed specifically for cryptocurrency mining. With a base clock of 1140MHz and a boost clock of 1410MHz, this GPU offers impressive performance for mining various cryptocurrencies. One of the standout features of the CMP 170HX is its generous 16GB of HBM2e memory, which enables efficient handling of large datasets and complex mining algorithms. The memory clock speed of 1458MHz further enhances its ability to quickly process and store data for mining operations. With 4480 shading units and 8MB of L2 cache, the CMP 170HX offers exceptional parallel processing capabilities, allowing for rapid and efficient computation of mining algorithms. Its TDP of 250W ensures that it can deliver consistent performance without overheating or drawing excessive power. In terms of theoretical performance, the CMP 170HX is capable of delivering an impressive 12.63 TFLOPS, making it well-suited for demanding mining tasks. Its high performance and robust design make it a reliable choice for cryptocurrency miners looking to maximize their mining efficiency. Overall, the NVIDIA CMP 170HX GPU is a powerhouse for cryptocurrency mining, offering exceptional performance, efficient memory handling, and reliable operation. Its impressive specifications make it a top choice for miners seeking a high-performing and dependable GPU for their mining operations.

Basic

Label Name
NVIDIA
Platform
Desktop
Launch Date
September 2021
Model Name
CMP 170HX
Generation
Mining GPUs
Base Clock
1140MHz
Boost Clock
1410MHz
Bus Interface
PCIe 4.0 x4
Transistors
54,200 million
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.
280
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.
280
Foundry
TSMC
Process Size
7 nm
Architecture
Ampere

Memory Specifications

Memory Size
16GB
Memory Type
HBM2e
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.
4096bit
Memory Clock
1458MHz
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.
1493 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.
180.5 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.
394.8 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.
50.53 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.
6.317 TFLOPS
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.
12.377 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.
70
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.
4480
L1 Cache
192 KB (per SM)
L2 Cache
8MB
TDP
250W
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.
N/A
OpenCL Version
3.0
OpenGL
N/A
DirectX
N/A
CUDA
8.0
Power Connectors
2x 8-pin
Shader Model
N/A
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.
128
Suggested PSU
600W

Benchmarks

FP32 (float)
Score
12.377 TFLOPS

Compared to Other GPU

FP32 (float) / TFLOPS
12.536 +1.3%
12.377
11.907 -3.8%
11.241 -9.2%