RESEARCH: CORE22-BENCHMARKING
FOLDING PROJECT #17102 PROFILE

This project tests a new computer program called core22 on different types of hardware. It uses short tasks to find any problems and make sure core22 works well on all computers.

This project contains a variety of benchmarking systems (with adjusted numbers of steps per system to give equal time/WU on an RTX 2080) to test and benchmark core22.

These WUs are very short and just used to detect issues with various hardware to ensure we can continue to improve core22 on all hardware.

benchmarking

The process of evaluating and comparing the performance of systems or components.

Benchmarking is a way to measure how well different computer hardware and software perform. It involves running tests and comparing the results to see which system is faster, more efficient, or better suited for a particular task. This helps developers and users make informed decisions about which products to choose.

hardware

The physical components of a computer system.

Hardware refers to the tangible parts of a computer that you can physically touch. This includes components like the processor (CPU), memory (RAM), storage drives (HDD or SSD), graphics card (GPU), motherboard, and input/output devices like keyboards, mice, and monitors.

RTX 2080

A high-performance graphics processing unit manufactured by NVIDIA.

The RTX 2080 is a powerful graphics card designed for gaming and other graphically intensive tasks. It features advanced technologies like ray tracing and DLSS to deliver realistic visuals and high frame rates.

core22

Likely refers to a specific version or iteration of a processor architecture.

Core22 could be a codename for a new generation of processors. Developers might use it internally to refer to their work on improving the performance and efficiency of this processor architecture.

work units (WUs)

Small, independent tasks assigned to computer processors in a distributed computing system.

Work units are tiny jobs that can be executed independently by different computers. This allows for parallel processing and efficient utilization of resources in large-scale computing projects.