NVIDIA RTX A1000
About GPU
The NVIDIA RTX A1000 GPU is a powerful desktop graphics card designed for professionals and enthusiasts alike. With a base clock of 727MHz and a boost clock of 1462MHz, this GPU offers excellent performance across a wide range of applications. The 8GB of GDDR6 memory and a memory clock of 1500MHz ensure smooth and efficient multitasking, making it an ideal choice for content creators, designers, and gamers.
The RTX A1000 packs an impressive 2304 shading units and 2MB of L2 cache, allowing for high-quality rendering and fast data processing. Additionally, with a TDP of 50W, this GPU strikes a good balance between performance and power efficiency, making it suitable for a variety of desktop setups.
One of the standout features of the RTX A1000 is its theoretical performance of 6.872 TFLOPS, allowing users to tackle demanding workloads with ease. Whether it's rendering complex 3D models or playing the latest AAA games, this GPU delivers smooth and consistent performance.
Overall, the NVIDIA RTX A1000 is an excellent choice for those in need of a high-performance GPU for their desktop. Its combination of powerful specs, efficient design, and versatile performance make it a worthy investment for professionals and gamers alike.
Basic
Label Name
NVIDIA
Platform
Desktop
Launch Date
April 2024
Model Name
RTX A1000
Generation
Quadro Ampere
Base Clock
727MHz
Boost Clock
1462MHz
Bus Interface
PCIe 4.0 x8
Memory Specifications
Memory Size
8GB
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.
128bit
Memory Clock
1500MHz
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.
192.0 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.
46.78 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.
105.3 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.
6.737 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.
105.3 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.
6.872
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.
18
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.
2304
L1 Cache
128 KB (per SM)
L2 Cache
2MB
TDP
50W
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
6.872
TFLOPS
OpenCL
Score
53439
Compared to Other GPU
FP32 (float)
/ TFLOPS
OpenCL