NVIDIA Tesla V100 PCIe 16 GB
About GPU
The NVIDIA Tesla V100 PCIe 16 GB GPU is a professional-grade graphics processing unit designed for high-performance computing tasks. With a base clock of 1245MHz and a boost clock of 1380MHz, this GPU offers exceptional speed and efficiency for a wide range of applications. With 16GB of HBM2 memory and a memory clock of 876MHz, the Tesla V100 PCIe provides ample memory bandwidth for handling large datasets and complex computations.
One of the standout features of the Tesla V100 PCIe is its impressive 5120 shading units, which allow for highly parallel processing and improved performance in rendering and simulation tasks. The inclusion of a 6MB L2 cache further enhances the GPU's ability to handle large workloads efficiently.
With a TDP of 300W, the Tesla V100 PCIe is a power-hungry GPU, but its high theoretical performance of 14.13 TFLOPS more than justifies its power consumption. This makes it an excellent choice for applications that require intense computational power, such as scientific simulations, deep learning, and artificial intelligence.
Overall, the NVIDIA Tesla V100 PCIe 16 GB GPU is a powerhouse of a graphics card that delivers exceptional performance and capabilities for professional users. Its high memory capacity, impressive shading units, and superior theoretical performance make it well-suited for demanding workloads in a variety of industries. While its power requirements are significant, the Tesla V100 PCIe's performance justifies the investment for users who require top-tier computational capabilities.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
June 2017
Model Name
Tesla V100 PCIe 16 GB
Generation
Tesla
Base Clock
1245MHz
Boost Clock
1380MHz
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
876MHz
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.
897.0 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.
176.6 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.
441.6 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.
28.26 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.
7.066 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.
14.413
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
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
14.413
TFLOPS
OctaneBench
Score
345
Compared to Other GPU
FP32 (float)
/ TFLOPS
OctaneBench