CUDA, But Make It AMD

Compute Unified Device Architecture, or CUDA, is a software platform for doing big parallel calculation tasks on NVIDIA GPUs. It’s been a big part of the push to use GPUs for general purpose computing, and in some ways, competitor AMD has thusly been left out in the cold. However, with more demand for GPU computation than ever, there’s been a breakthrough. SCALE from [Spectral Compute] will let you compile CUDA applications for AMD GPUs.

SCALE allows CUDA programs to run as-is on AMD GPUs, without modification. The SCALE compiler is also intended as a drop-in swap for nvcc, right down to the command line options. For maximum ease of use, it acts like you’ve installed the NVIDIA Cuda Toolkit, so you can build with cmake just like you would for a normal NVIDIA setup. Currently, Navi 21 and Navi 31 (RDNA 2.0 and RDNA 3.0) targets are supported, while a number of other GPUs are undergoing testing and development.

The basic aim is to allow developers to use AMD hardware without having to maintain an entirely separate codebase. It’s still a work in progress, but it’s a promising tool that could help break NVIDIA’s stranglehold on parts of the GPGPU market.

 

GPU Processing And Password Cracking

Recently, research students at Georgia Tech released a report outlining the dangers that GPUs pose to the current state of password security. There are a number of ways to crack a password, all with their different pros and cons, but when it comes down to it, the limiting factor in all of these methods is processing complexity. The more operations that need to be run, the longer it takes, and the less useful each tool is for cracking passwords. In the past, most recommendations for password security revolved around making sure your password wasn’t something predictable, such as “password” or your birthday. With today’s (and tomorrows) GPUs, this may no longer be enough.

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