NVIDIA Tesla M2070 Q
About GPU
The NVIDIA Tesla M2070 Q GPU is a powerful and high-performance professional graphics card designed for professional and scientific computing applications. With a generous 6GB of GDDR5 memory, a memory clock speed of 783MHz, and 448 shading units, this GPU delivers exceptional performance for a wide range of computational tasks.
One of the standout features of the Tesla M2070 Q is its impressive 1.028 TFLOPS of theoretical performance, making it ideal for demanding workloads such as data analytics, machine learning, and scientific simulations. The 768KB L2 cache helps to further optimize performance by reducing latency and increasing throughput.
In addition to its impressive performance capabilities, the Tesla M2070 Q is also designed with power efficiency in mind, with a TDP of 225W. This makes it a suitable choice for organizations looking to minimize their environmental impact and energy costs while still benefiting from high-performance computing capabilities.
Overall, the NVIDIA Tesla M2070 Q GPU is a superb choice for professionals and researchers working in fields that require intense computational power. With its generous memory size, high memory bandwidth, and efficient power usage, this GPU offers an excellent balance of performance and power efficiency for a variety of professional computing applications. Whether used for academic research, scientific simulations, or data analytics, the Tesla M2070 Q is a reliable and powerful choice for professionals in need of high-performance computing capabilities.
Basic
Label Name
NVIDIA
Platform
Professional
Launch Date
July 2011
Model Name
Tesla M2070 Q
Generation
Tesla
Bus Interface
PCIe 2.0 x16
Memory Specifications
Memory Size
6GB
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.
384bit
Memory Clock
783MHz
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.
150.3 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.
16.07 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.
32.14 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.
513.9 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.
1.007
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.
14
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.
448
L1 Cache
64 KB (per SM)
L2 Cache
768KB
TDP
225W
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.
N/A
OpenCL Version
1.1
Benchmarks
FP32 (float)
Score
1.007
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS