NVIDIA Tesla P4
About GPU
The NVIDIA Tesla P4 GPU is a professional-grade graphics processing unit designed for a range of workloads including deep learning inference and machine learning applications. With a base clock speed of 886MHz and a boost clock of 1114MHz, the Tesla P4 offers impressive performance for a variety of compute-intensive tasks. The 8GB of GDDR5 memory with a memory clock of 1502MHz provides ample resources for handling large datasets and complex calculations.
One of the standout features of the Tesla P4 is its efficient power usage, with a thermal design power (TDP) of just 75W. This low power consumption makes it an excellent choice for deployment in data centers and other enterprise environments where energy efficiency is a priority.
With 2560 shading units and 2MB of L2 cache, the Tesla P4 is capable of handling demanding workloads with ease, delivering a theoretical performance of 5.704 TFLOPS. This makes it well-suited for deep learning inference tasks, video transcoding, and other high-performance computing applications.
Overall, the NVIDIA Tesla P4 GPU is a compelling choice for professionals and enterprises in need of a powerful and efficient solution for a wide range of compute-intensive tasks. Its impressive performance, low power consumption, and generous memory capacity make it a highly versatile and capable option for demanding workloads.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
September 2016
Model Name
Tesla P4
Generation
Tesla
Base Clock
886MHz
Boost Clock
1114MHz
Bus Interface
PCIe 3.0 x16
Memory Specifications
Memory Size
8GB
Memory Type
GDDR5
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
1502MHz
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.
192.3 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.
71.30 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.
178.2 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.
89.12 GFLOPS
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.
178.2 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.
5.59
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.
20
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.
2560
L1 Cache
48 KB (per SM)
L2 Cache
2MB
TDP
75W
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
5.59
TFLOPS
Blender
Score
429
OctaneBench
Score
93
Compared to Other GPU
FP32 (float)
/ TFLOPS
Blender
OctaneBench