NVIDIA Tesla P100 DGXS
About GPU
The NVIDIA Tesla P100 DGXS GPU is a powerful and efficient professional-grade graphics processing unit. With a base clock of 1328MHz and a boost clock of 1480MHz, it offers impressive performance for a wide range of computational tasks. The 16GB of HBM2 memory and a memory clock of 715MHz provide ample capacity and speed for handling large datasets and complex simulations. The 3584 shading units and 4MB L2 cache further contribute to its ability to efficiently process and render high-resolution graphics and models.
One of the standout features of the Tesla P100 DGXS is its exceptional theoretical performance, boasting 10.61 TFLOPS, which makes it well suited for demanding workloads in fields such as artificial intelligence, deep learning, and scientific computing. The 300W TDP ensures that the GPU operates reliably and efficiently under heavy loads, making it a dependable choice for continuous, intensive use.
Overall, the NVIDIA Tesla P100 DGXS GPU offers exceptional performance, reliability, and efficiency for professional applications. Its high memory capacity, fast memory speeds, and impressive theoretical performance make it an excellent choice for professionals and organizations seeking a powerful and versatile GPU for demanding computational tasks. Whether it's for machine learning, data analysis, or scientific research, the Tesla P100 DGXS is a top-of-the-line solution for professionals in need of high-performance computing capabilities.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
April 2016
Model Name
Tesla P100 DGXS
Generation
Tesla
Base Clock
1328MHz
Boost Clock
1480MHz
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.
142.1 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.
331.5 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.
21.22 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.
5.304 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.
10.398
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
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
10.398
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS