NVIDIA Tesla T10
About GPU
The NVIDIA Tesla T10 GPU is a powerful and high-performance graphics processing unit designed for professional use. With a base clock speed of 1305MHz and a boost clock speed of 1560MHz, this GPU is capable of delivering exceptional performance for a wide range of professional applications.
One of the most impressive features of the Tesla T10 is its massive 24GB of GDDR6 memory, which allows for large and complex datasets to be processed with ease. In addition, the 4608 shading units and 6MB of L2 cache further contribute to the GPU's ability to handle demanding workloads.
The TDP of 260W may be on the higher end, but it is a necessary trade-off for the immense processing power and theoretical performance of 14.38 TFLOPS that this GPU offers. These impressive specifications make the Tesla T10 an ideal choice for professionals working in fields such as data analysis, scientific research, and AI development.
Furthermore, the T10's support for a wide range of professional applications, including machine learning, deep learning, and high-performance computing, makes it a versatile and valuable tool for professionals in need of cutting-edge processing power.
In conclusion, the NVIDIA Tesla T10 GPU is a top-of-the-line solution for professionals seeking uncompromising performance and reliability. With its impressive specifications and robust performance capabilities, it is well-suited for a wide range of professional applications and workloads.
Basic
Label Name
NVIDIA
Platform
Professional
Model Name
Tesla T10
Generation
Tesla
Base Clock
1305MHz
Boost Clock
1560MHz
Bus Interface
PCIe 3.0 x16
Memory Specifications
Memory Size
24GB
Memory Type
GDDR6
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.
384bit
Memory Clock
1625MHz
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.
624.0 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.
149.8 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.
449.3 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.
28.75 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.
449.3 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.
14.668
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.
72
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.
4608
L1 Cache
64 KB (per SM)
L2 Cache
6MB
TDP
260W
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
14.668
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS