NVIDIA Tesla P100 PCIe 16 GB

NVIDIA Tesla P100 PCIe 16 GB

About GPU

The NVIDIA Tesla P100 PCIe 16 GB GPU is a powerful professional-grade GPU designed for high-performance computing and deep learning applications. With a base clock of 1190MHz and a boost clock of 1329MHz, this GPU provides blistering fast processing speeds to handle the most demanding workloads. The 16GB of HBM2 memory and a memory clock of 715MHz ensure that the GPU has ample memory bandwidth to handle large datasets and complex calculations. The 3584 shading units and 4MB of L2 cache further enhance the GPU's ability to handle parallel processing tasks efficiently. One of the standout features of the Tesla P100 is its impressive theoretical performance of 9.526 TFLOPS, making it well-suited for machine learning, artificial intelligence, and other compute-intensive tasks. Additionally, the TDP of 250W ensures that the GPU can maintain high levels of performance without overheating or consuming excessive power. In practical terms, the Tesla P100 excels in tasks such as machine learning training, data analysis, and scientific simulations. Its high memory capacity and bandwidth make it well-suited for handling large-scale deep learning models and datasets. Overall, the NVIDIA Tesla P100 PCIe 16 GB GPU is a top-of-the-line solution for professionals and organizations that require uncompromising performance for their compute-intensive workloads. Its combination of high clock speeds, generous memory capacity, and efficient power usage make it a standout option for those in need of the best performance for their applications.

Basic

Label Name
NVIDIA
Platform
Professional
Launch Date
June 2016
Model Name
Tesla P100 PCIe 16 GB
Generation
Tesla
Base Clock
1190MHz
Boost Clock
1329MHz
Bus Interface
PCIe 3.0 x16

Memory Specifications

Memory Size
16GB
Memory Type
HBM2
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
715MHz
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.
732.2 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.
127.6 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.
297.7 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.
19.05 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.
4.763 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.
9.335 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.
56
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.
3584
L1 Cache
24 KB (per SM)
L2 Cache
4MB
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.
1.3
OpenCL Version
3.0

Benchmarks

FP32 (float)
Score
9.335 TFLOPS
Blender
Score
1200
OctaneBench
Score
217

Compared to Other GPU

FP32 (float) / TFLOPS
9.432 +1%
Blender
1256 +4.7%
1222 +1.8%
1154 -3.8%