NVIDIA has a new Ampere-based GPU announced today alongside SIGGRAPH 2021. The new NVIDIA RTX A2000 GPU aims to bring a lower power and cost point to the Ampere generation. For those confused by the naming, the RTX A2000 would have previously been called a “Quadro” however the Quadro brand for workstation GPUs and Tesla brand for data center GPUs were retired. We covered this in Confirmed NVIDIA Quadro Branding Phased Out for New Products if you want to learn more.
NVIDIA RTX A2000 GPU
The NVIDIA RTX A2000 is an 8nm Samsung Ampere GPU, but it is designed for a lower power footprint than many of the other options. First off, it is designed to be a low-profile PCIe Gen4 x16 card which means it can fit in many compact workstations.
In terms of memory, we get 6GB of GDDR6 with ECC and a 192-bit memory interface good for up to 288GB/s. The 276mm2 die has 13.25 billion transistors and 3328 CUDA cores, 104 Tensor cores, and 26 RT cores. This gives the solution the ability to do 8 TFLOPS of single-precision, 69.9 TFLOPS on the Tensor cores, and 15.6 TFOPS on the RT cores. We did not get double precision figures on the pre-brief for the card. There is also a NVENC and NVDEC onboard with AV1 decode.
The card uses a dual-slot active cooler and is a 70W card meaning it does not need external power connectivity instead drawing power from the PCIe Gen4 x16 bus. For graphics, there are four miniDP 1.4 ports.
While big GPUs get a lot of attention, and for good reason, the trend towards AI inference and GPU acceleration being used by more applications is clear. NVIDIA along with AMD and Intel are racing to add GPU acceleration and AI inference to more edge systems. Intel has been adding DL Boost AI inference instructions as well as pushing its Xe graphics for this and NVIDIA cannot ignore this market. The RTX A2000 is a major step in the right direction here. While it may not be the fastest card on the market, getting Ampere-based compute to lower-end price points and smaller form factors is important for OEM adoption and inclusion in configurations.