More Money Is Waiting For You Thanks To The NVIDIA RTX A30 24GB Mining Hashrate
All enterprise workloads, including mining, are accelerated by the NVIDIA RTX A30 24GB Mining Hashrate. As a result of the NVIDIA Ampere architecture and Multi-Instance GPU, it is capable of accelerating a wide range of workloads, from AI inference to HPC applications at scale. An adaptable data center and maximum value for businesses are enabled by A30's combination of rapid memory bandwidth and low power consumption in a PCIe form factor.
NVIDIA A30 Tensor Cores with Tensor Float (TF32) give up to 10X higher performance over the NVIDIA T4 with no code changes and an additional 2X boost with automated mixed precision and FP16, resulting in a combined 20X throughput gain. As many as tens of thousands of GPUs can be supported when using the NVIDIA Magnum IO SDK, NVIDIA NVLink, PCIe Gen4, and NVIDIA networking.
As a result of Tensor Cores and MIG, A30 can be used for a wide range of workloads throughout the day. A portion of the GPU can be repurposed during off-peak hours to swiftly retrain the same models used for inference during high demand.
Learn more about the mining hashrate and characteristics of the NVIDIA RTX A30 GPU by reading on.
- Peak FP64: 5.2 TFLOPS
- Peak FP64 Tensor Core: 10.3 TFLOPS
- Peak FP32: 10.3 TFLOPS
- TF32 Tensor Core: 82 TFLOPS | 165 TFLOPS
- BFLOAT16 Tensor Core: 165 TFLOPS | 330 TFLOPS
- Peak FP16 Tensor Core: 165 TFLOPS | 330 TFLOPS
- Peak INT8 Tensor Core: 330 TOPS | 661 TOPS*
- GPU Memory: 24 GB HBM2
- Memory Bandwidth: 933 GB/s
- Thermal Solutions: Passive
- Maximum Power Consumption: 165 W
- System Interface: PCIe Gen 4.0 | 64 GB/s
- Multi-Instance GPU Support: Yes
- vGPU Support: Yes
- DaggerHashimoto [ EtHash : (ETH) & (ETC) ] Ethereum Mining Hashrate : 102 MH/s
Power Consumption: 140 Watts/Hour
- SPIDER ETH-102 MH/s
- BINANCE ETH-102 MH/s
- F2POOL ETH-102 MH/s
- FLEXPOOL ETH-102 MH/s
- EZIL ETH-102 MH/s
- 2MINERS ETH-102 MH/s
- HIVEON ETH-102 MH/s
- POOLIN ETH-102 MH/s
- NH Ethash-102 MH/s
- VIABTC ETH-102 MH/s
NVIDIA A30 Tensor Core GPU for Inference - Everything You Need To Know
The NVIDIA A30 is equipped with FP64 technology. This is the biggest gain in HPC performance since the introduction of graphics processing units (GPUs). Researchers can quickly solve double-precision computations using 24 terabytes of GPU memory with a bandwidth of 933 gigabytes per second (GB/s). Single-precision, dense matrix-multiply operations in HPC can also benefit from TF32's greater throughput.
It is possible to partition the GPU using FP64 Tensor Cores and MIG in order to guarantee the quality of service and maximize the utilization of the GPU. Businesses can employ A30 during peak demand periods, then repurpose the same servers for high-performance computing (HPC) or artificial intelligence (AI) development when demand is less high.