NVIDIA Tesla P100 PCIe 12 GB
About GPU
The NVIDIA Tesla P100 PCIe 12 GB GPU is a high-performance professional computing platform that delivers exceptional power and efficiency for a variety of computational tasks. With a base clock of 1190MHz and a boost clock of 1329MHz, this GPU offers impressive processing capabilities that can handle even the most demanding workloads.
One of the standout features of the Tesla P100 is its large 12GB of HBM2 memory, which provides ample capacity for handling large datasets and complex simulations. The memory clock speed of 715MHz ensures fast and reliable access to data, while the 3584 shading units enable parallel processing for increased efficiency.
In terms of power efficiency, the Tesla P100 boasts a TDP of 250W, making it a suitable choice for environments where energy consumption is a concern. Despite its lower power consumption, this GPU offers a theoretical performance of 9.526 TFLOPS, making it an ideal choice for deep learning, high-performance computing, and other compute-intensive tasks.
Additionally, the Tesla P100 features 3MB of L2 cache, which helps to accelerate data processing and reduce latency. This, combined with its high-performance architecture, makes it a versatile and reliable choice for professionals who require exceptional computing power.
Overall, the NVIDIA Tesla P100 PCIe 12 GB GPU stands out as a top-tier professional computing platform, offering a potent combination of performance, efficiency, and memory capacity. Whether used for AI research, scientific simulations, or other demanding applications, this GPU delivers the power and reliability needed to tackle complex computational tasks with ease.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
June 2016
Model Name
Tesla P100 PCIe 12 GB
Generation
Tesla
Base Clock
1190MHz
Boost Clock
1329MHz
Bus Interface
PCIe 3.0 x16
Memory Specifications
Memory Size
12GB
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.
3072bit
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.
549.1 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.
9.717
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
3MB
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
9.717
TFLOPS
Blender
Score
920
Compared to Other GPU
FP32 (float)
/ TFLOPS
Blender