NVIDIA Tesla PG503 216

NVIDIA Tesla PG503 216

About GPU

The NVIDIA Tesla PG503 216 GPU is a professional-grade graphics processing unit that delivers exceptional performance for demanding workloads. With a base clock of 1312MHz and a boost clock of 1530MHz, this GPU is capable of handling intensive tasks with ease. The 32GB of HBM2 memory provides ample space for storing and accessing large datasets, while the memory clock of 1106MHz ensures quick data transfers. One of the standout features of the Tesla PG503 216 GPU is its impressive 5120 shading units, which enable it to handle complex graphics rendering and compute tasks efficiently. Additionally, the 6MB L2 cache helps to reduce latency and improve overall system performance. With a TDP of 250W, this GPU strikes a balance between power consumption and high performance. It is well-suited for professional applications such as AI training, data analytics, and scientific simulations. In terms of raw computing power, the Tesla PG503 216 GPU offers a theoretical performance of 15.67 TFLOPS, making it a powerhouse for parallel processing tasks. Overall, the NVIDIA Tesla PG503 216 GPU is a top-of-the-line solution for professionals who require unmatched performance and reliability. Whether you are a data scientist, AI researcher, or engineer, this GPU has the capabilities to accelerate your workflow and tackle the most demanding computing tasks.

Basic

Label Name
NVIDIA
Platform
Professional
Launch Date
November 2019
Model Name
Tesla PG503 216
Generation
Tesla
Base Clock
1312MHz
Boost Clock
1530MHz
Bus Interface
PCIe 3.0 x16

Memory Specifications

Memory Size
32GB
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
1106MHz
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.
1133 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.
195.8 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.
489.6 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.
31.33 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.
7.834 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.
15.357 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.
80
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.
5120
L1 Cache
128 KB (per SM)
L2 Cache
6MB
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
15.357 TFLOPS

Compared to Other GPU

FP32 (float) / TFLOPS
14.602 -4.9%
13.994 -8.9%