NVIDIA Tesla K8
About GPU
The NVIDIA Tesla K8 GPU is a powerful professional platform GPU designed for high-performance computing and deep learning applications. With a base clock of 693MHz and a boost clock of 811MHz, the Tesla K8 delivers impressive processing power for complex computational tasks.
Equipped with 8GB of GDDR5 memory and a memory clock of 1250MHz, the Tesla K8 is capable of handling large datasets and processing high-resolution graphics with ease. The GPU features 1536 shading units and 512KB of L2 cache, which contribute to its impressive computational capabilities.
One of the standout features of the Tesla K8 is its energy efficiency, with a TDP of 100W. This means that the GPU delivers high performance while also being mindful of power consumption, making it a great choice for data centers and other large-scale computing environments.
With a theoretical performance of 2.491 TFLOPS, the Tesla K8 is well-suited for demanding workloads, such as scientific simulations, molecular modeling, and machine learning tasks. Its robust performance and efficiency make it a valuable tool for researchers, data scientists, and engineers who require a reliable and high-performance GPU for their work.
Overall, the NVIDIA Tesla K8 GPU offers impressive performance, energy efficiency, and reliability, making it an excellent choice for professionals working with complex computational tasks. Whether used for simulation, data analysis, or deep learning, the Tesla K8 delivers the power and efficiency required for demanding computing applications.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
September 2014
Model Name
Tesla K8
Generation
Tesla
Base Clock
693MHz
Boost Clock
811MHz
Bus Interface
PCIe 2.0 x16
Transistors
3,540 million
TMUs
?
Texture Mapping Units (TMUs) serve as components of the GPU, which are capable of rotating, scaling, and distorting binary images, and then placing them as textures onto any plane of a given 3D model. This process is called texture mapping.
128
Foundry
TSMC
Process Size
28 nm
Architecture
Kepler
Memory Specifications
Memory Size
8GB
Memory Type
GDDR5
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.
256bit
Memory Clock
1250MHz
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.
160.0 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.
25.95 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.
103.8 GTexel/s
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.
103.8 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.
2.441
TFLOPS
Miscellaneous
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.
1536
L1 Cache
16 KB (per SMX)
L2 Cache
512KB
TDP
100W
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.
1.1
OpenCL Version
3.0
OpenGL
4.6
DirectX
12 (11_0)
CUDA
3.0
Power Connectors
1x 6-pin
Shader Model
5.1
ROPs
?
The Raster Operations Pipeline (ROPs) is primarily responsible for handling lighting and reflection calculations in games, as well as managing effects like anti-aliasing (AA), high resolution, smoke, and fire. The more demanding the anti-aliasing and lighting effects in a game, the higher the performance requirements for the ROPs; otherwise, it may result in a sharp drop in frame rate.
32
Suggested PSU
300W
Benchmarks
FP32 (float)
Score
2.441
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS