AMD Radeon Pro V340
About GPU
The AMD Radeon Pro V340 is a high-performance GPU that is specifically designed for use in desktop workstations. With a base clock speed of 852MHz and a boost clock speed of 1500MHz, this GPU is capable of delivering exceptional graphical performance across a wide range of applications.
One of the standout features of the Radeon Pro V340 is its generous 16GB of HBM2 memory. This high-bandwidth memory type, combined with a memory clock speed of 945MHz, ensures that the GPU is able to handle large, complex datasets with ease. This makes it an ideal choice for professionals working in fields such as 3D rendering, virtual reality, and scientific visualization.
In terms of raw processing power, the Radeon Pro V340 is no slouch. With 3584 shading units and 4MB of L2 cache, this GPU is capable of delivering a theoretical performance of 10.75 TFLOPS. This level of performance makes it well-suited for demanding workloads, such as real-time 3D modeling and simulation.
It is worth noting that the Radeon Pro V340 does come with a relatively high TDP of 230W, so users will need to ensure that their workstation is equipped to handle the power requirements of this GPU.
Overall, the AMD Radeon Pro V340 is a powerhouse GPU that is well-suited to a wide range of professional applications. With its generous memory size, high memory bandwidth, and impressive theoretical performance, it is sure to meet the needs of even the most demanding users.
Basic
Label Name
AMD
Platform
Desktop
Launch Date
August 2018
Model Name
Radeon Pro V340
Generation
Radeon Pro
Base Clock
852MHz
Boost Clock
1500MHz
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.
2048bit
Memory Clock
945MHz
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.
483.8 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.
96.00 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.
336.0 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.
21.50 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.
672.0 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.
10.965
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.
3584
L1 Cache
16 KB (per CU)
L2 Cache
4MB
TDP
230W
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.
1.2
OpenCL Version
2.1
Benchmarks
FP32 (float)
Score
10.965
TFLOPS
Compared to Other GPU
FP32 (float)
/ TFLOPS