There have been ongoing conversations as to the possibility of using Field Programmable Gate Arrays (FPGAs) to crack passwords. The answer is both yes and no – FPGAs may or may not be used for this purpose.

Find out in this blog post, how possible it would be to crack passwords or not using Field Programmable Gate Arrays (FPGAs).

The FPGA Hashcat Perspective

This was the earliest proposal for cracking passwords with the aid of FPGAs. It has to do with the combination of Field Programmable Gate Array (FPGA) and Hashcat.

The idea is to leverage the fusion of the two and the remodification capabilities of the FPGA’s ICs to facilitate password hacking.

Today, FPGA Hashcat has given way to newer methods. Some of the reasons for the limited usage are the high-end hardware required for the process, lengthened compilation time (assuming the FPGAs were compatible with OpenCL) and need to repeat the processes after each successful hack.

What Next?

The reduced dependence on FPGA Hashcat can be attributed to the newer technologies used for FPGA crack. The most popular is the use of FPGA Clusters.

What are FPGA Clusters?

They are the combination of different Field Programmable Gate Arrays (FPGAs), with the purpose of accelerating code/password cracking and cryptographic algorithms.

How to Crack Codes and Passwords with FPGA Clusters

Based on previous studies, it has been ascertained that a cluster of commodity Field Programmable Gate Arrays (FPGAs), when placed in a single 4U chassis, can be able to deliver up to 2,000 dual-core processors worth of computational power.

This is, of course, subject to the fact that the single 4U chassis consumes less power, typically under 1,400 watts.

Why FPGA Clusters are Popularly Used for Code Cracking

There are a couple of reasons that suggest why the use of clusters of FPGAs can make a lot of differences in cracking codes.

Here are some of the reasons:

Chassis-Fitting

Due to the requirement for the clusters to be used with the 4U chassis; it makes sense to use something that fits.

FPGAs comfortably fit into the chassis. This, in turn, gives room for the forensic users to easily construct the racks stuffed with the FPGA-based systems.

Better Optimization

You want to work with a tool that assures of the best FPGA crack solutions. That is what you get from using the FPGA clusters.

Here is why it matters:

• The clusters of FPGAs tend to offer a significant performance more than the Graphics Processing Units (GPUs) do.
• You can also use the clusters for specific tasks, such as recovering passwords.

Excellent Power Management

It is one thing to use FPGA crack methods to obtain passwords and crack codes. It is an entirely different thing to use the same method effectively.

You can be sure to maximize power with the clusters of FPGAs, as they consume less power and don’t generate much heat.

Important Considerations for FPGA Clusters

Using clusters of Field Programmable Gate Arrays (FPGAs) is not without some stresses. Here are some of the things to consider before making the decision to use them:

• Field Programmable Gate Array (FPGA) clusters tend to cost more per teraflop of performance they bring forth.
• The clusters do not support all the software algorithms.

GPU Clusters – Another Option Worth Exploring

Besides the clusters of FPGAs, it is also possible to use the clusters of Graphics Processing Units (GPUs).

Here are a couple of quick takes before we delve into the discussion:

• These clusters are based on GPU-accelerated workstations.
• They are also based on consumer-grade video cards.
• GPU clusters are used for a variety of purposes, such as cracking the passwords used to protect Wi-Fi communication systems. The clusters also aid the cracking of passwords stored in Apple devices and those used to protect office-related databases.

How the GPU Clusters Work

These clusters are regarded as a faster route to obtaining passwords and cracking codes. They can also be cost-saving in some way.

Here is the rest of the things you need to know about using GPUS clusters instead of FPGAs for code cracking purposes:

Significant Performance Boost

One of the important considerations for cracking code and hacking/obtaining passwords is speed. If the process is sped up, you will be through in the shortest time possible.

If that is the case, you can rely on the clusters of GPUs, due to the speed of the graphic cards – especially those based on the Graphics Core Next architecture by AMD.

The other aspects of GPU clusters’ acceleration capabilities include:

• The support for thousands of stream processors.
• A cluster of 4 graphics cards (either from NVIDIA or AMD) potentially provides up to 1000 dual-core Central Processing Units (CPUs) in a single chassis.

Downsides to GPU Clusters

Despite relegating traditional CPU usage to the background, GPU clusters are still not completely free of some challenges.

The major downsides include non-optimization for the task of recovering passwords.

FPGA Clusters vs. GPU Clusters

Both the clusters of Field Programmable Gate Arrays (FPGAs) and Graphics Processing Units (GPUs) have distinct benefits. On a closer look, one can see that the FPGA clusters have the upper hand.

Here is how they compare:

Heat Generation

When a cluster of 4 graphics (video gaming) cards is installed in a single computer, there is a chance of increased heat generation. Depending on the card, the power it sucks could be up to 300 watts.

This is higher, when compared to the less heat generated when using the FPGA clusters. These clusters provide up to 2,000 dual-core processors of computational power, without sacrificing excess heat generation.

Cost Considerations

The GPU clusters are you go-to for savings costs when cracking codes and recovering passwords. They cost less per teraflop of performance than the FPGA clusters do.

Conclusion

Field Programmable Gate Arrays (FPGAs) are becoming faster than the GPU clusters are. With the reduced heat generation, the improved performance and the optimizations, there is no doubt that you can use these to crack codes faster.