Explore DataCrunch's A100_80G cloud instance specifications and benchmarks. Compare hardware configurations and performance metrics to optimize your AI and ML workloads.
Hardware Specifications
| GPU Configuration | Value |
|---|---|
| GPU Type | A100_80G |
| GPU Interconnect | SXM4 |
| GPU Model Name | NVIDIA A100-SXM4-80GB |
| Driver Version | 570.86.15 |
| GPU VRAM | 160 GB |
| Power Limit (W) | 400.00 |
| GPU Temperature (°C) | 26 |
| GPU Clock Speed (MHz) | 210 |
| Memory Clock Speed (MHz) | 1593 |
| Pstate | P0 |
| CPU Configuration | Value |
|---|---|
| Model Name | AMD EPYC 7642 48-Core Processor |
| Vendor ID | AuthenticAMD |
| CPUs | 44 |
| CPU Clock Speed | 4591.37 |
| Threads Per Core | 1 |
| Cores Per Socket | 1 |
| Sockets | 44 |
| Memory | Value |
|---|---|
| Total | 235Gb |
Disks Specifications
| Storage | Value |
|---|---|
| Total | 500.00 GB |
Available Disks
| Property | Value |
|---|---|
| Disk 1 | |
| Model | vda |
| Size | 500Gb |
| Type | HDD |
| Mount Point | Unmounted |
Software Specifications
| Software | Value |
|---|---|
| OS | Ubuntu |
| OS Version | 22.04.5 LTS (Jammy Jellyfish) |
| Cuda Driver | 12.8 |
| Docker Version | 27.5.1 |
| Python Version | Python 3.10.12 |
Benchmarks
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| Benchmark | Value |
|---|---|
| ffmpeg | 92ms |
| Coremark (Iterations per sec) | 25313.251 |
| llama2Inference (Tokens per sec) | 40.02 |
| Tensorflow Mnist Training | 3.425 |