What is Tesla K80 equivalent?
We believe that the nearest equivalent to Tesla K80 from AMD is Radeon Pro W5500M.
What is Nvidia Tesla K80 used for?
The NVIDIA® Tesla® K80 Accelerator dramatically lowers data center costs by delivering exceptional performance with fewer, more powerful servers. It’s engineered to boost throughput in real-world applications by 5-10x, while also saving customers up to 50% for an accelerated data center compared to a CPU-only system.
How powerful is a Tesla K80?
Meet the Tesla K80: Nvidia’s most powerful graphics card yet has an insane 24GB of RAM. The K80 delivers 8.74 teraflops of single-precision performance compared to 5 teraflops on Nvidia’s flagship GeForce GTX 980 desktop graphics card.
Is Nvidia Tesla K80 good for deep learning?
Deep Learning Benchmark Conclusions The single-GPU benchmark results show that speedups over CPU increase from Tesla K80, to Tesla M40, and finally to Tesla P100, which yields the greatest speedups (Table 5, Figure 1) and fastest runtimes (Table 6).
How many TFLOPs is RTX 3080?
34.1 TFLOPS
NVIDIA Quietly Launches GeForce RTX 3080 12GB: More VRAM, More Power, More Money
| NVIDIA GeForce Specification Comparison | ||
|---|---|---|
| RTX 3080 Ti | RTX 3070 Ti | |
| Memory Bus Width | 384-bit | 256-bit |
| VRAM | 12GB | 8GB |
| Single Precision Perf. | 34.1 TFLOPS | 21.7 TFLOPS |
What is NVIDIA Tesla good for?
You may already know NVIDIA Tesla as a line of GPU accelerator boards optimized for high-performance, general-purpose computing. They are used for parallel scientific, engineering, and technical computing, and they are designed for deployment in supercomputers, clusters, and workstations.
How many CUDA cores are in K80?
4992 CUDA cores
The K80 is a dual GPU unit which utilizes two GK210B chipsets. As a unit this card offers a total of 4992 CUDA cores clocked at 560 MHz coupled to 24GB of GDDR5 vRAM with a 384-bit memory interface and a 480 GB/s bandwidth.
How fast is a Nvidia K80?
The GPU is operating at a frequency of 562 MHz, which can be boosted up to 824 MHz, memory is running at 1253 MHz (5 Gbps effective). Being a dual-slot card, the NVIDIA Tesla K80 draws power from 1x 8-pin power connector, with power draw rated at 300 W maximum.
Which GPU is best for AI?
Top 10 GPUs for Deep Learning in 2021
- NVIDIA Tesla K80.
- The NVIDIA GeForce GTX 1080.
- The NVIDIA GeForce RTX 2080.
- The NVIDIA GeForce RTX 3060.
- The NVIDIA Titan RTX.
- ASUS ROG Strix Radeon RX 570.
- NVIDIA Tesla V100.
- NVIDIA A100. The NVIDIA A100 allows for AI and deep learning accelerators for enterprises.
How many TFLOPs is RTX 3090?
According to Nvidia, the RTX 3090 Ti is capable of 40 shader TFLOPs, 78 RT TFLOPs, and 320 Tensor TFLOPs. For perspective, the RTX 3090 offers 36 shader TFLOPs, 69 RT TFLOPs, and 285 Tensor TFLOPs.
How many teraflops is 2060?
Nonetheless, the GeForce RTX 2060 12GB does offer higher FP32 performance. The regular version is rated for 6.5 TFLOPs, and this 12GB variant offers 7.2 TFLOPs, a 10.8% uplift.
What is the Tesla K80?
The Tesla K80 was a professional graphics card by NVIDIA, launched in November 2014. Built on the 28 nm process, and based on the GK210 graphics processor, in its GK210-885-A1 variant, the card supports DirectX 12. The GK210 graphics processor is a large chip with a die area of 561 mm² and 7,100 million transistors.
How many GK210 GPUs does the Tesla K80 accelerator have?
The Tesla K80 Accelerator has two Tesla GK210 GPUs. Characteristics for both GPUs are as follows: Number of processor cores: 2496 Base core clock: 560 MHz Boost clocks: 562 MHz to 875 MHz
Why did Nvidia stop making Tesla GPUs?
The Nvidia Tesla product line competed with AMD’s Radeon Instinct and Intel Xeon Phi lines of deep learning and GPU cards. Nvidia retired the Tesla brand in May 2020, reportedly because of potential confusion with the brand of cars. Its new GPUs are branded Nvidia Data Center GPUs, as in the Ampere A100 GPU.
What is the meaning of Nvidia Tesla?
Nvidia Tesla was the name of Nvidia’s line of products targeted at stream processing or general-purpose graphics processing units (GPGPU), named after pioneering electrical engineer Nikola Tesla. Its products began using GPUs from the G80 series, and have continued to accompany the release of new chips.