Archive for July 17th, 2012

Accelerating Password Recovery: the Addition of FPGA

Tuesday, July 17th, 2012

Back in 2008, ElcomSoft started using consumer-grade video cards to accelerate password recovery. The abilities of today’s GPU’s to perform massively parallel computations helped us greatly increase the speed of recovering passwords. Users of GPU-accelerated ElcomSoft password recovery tools were able to see the result 10 to 200 times (depending on system configuration) sooner than the users of competing, non-accelerated products.

Today, ElcomSoft introduced support for a new class of acceleration hardware: Field Programmable Gate Arrays (FPGAs) used by Pico Computing in its hardware acceleration modules. Two products have received the update: Elcomsoft Phone Password Breaker and Elcomsoft Wireless Security Auditor, enabling accelerated recovery of Wi-Fi WPA/WPA2 passwords as well as passwords protecting Apple and Blackberry offline backups. In near future, Pico FPGA support will be added to Elcomsoft Distributed Password Recovery.

With FPGA support, ElcomSoft products now support a wide range of hardware acceleration platforms including Pico FPGA’s, OpenCL compliant AMD video cards, Tableau TACC, and NVIDIA CUDA compatible hardware including conventional and enterprise-grade solutions such as Tesla and Fermi.

Hardware Acceleration of Password Recovery
Today, no serious forensic user will use a product relying solely on computer’s CPU. Clusters of GPU-accelerated workstations are employed to crack a wide range of passwords from those protecting office documents and databases to passwords protecting Wi-Fi communications as well as information stored in Apple and BlackBerry smartphones. But can consumer-grade video cards be called the definite ‘best’ solution?

GPU Acceleration: The Other Side of the Coin
Granted, high-end gaming video cards provide the best bang for the buck when it comes to buying teraflops. There’s simply no competition here. A cluster of 4 AMD or NVIDIA video cards installed in a single chassis can provide a computational equivalent of 500 or even 1000 dual-core CPU’s at a small fraction of the price, size and power consumption of similarly powerful workstation equipped only with CPU’s.

However, GPU’s used in video cards, including enterprise-grade solutions such as NVIDIA Tesla, are not optimized for the very specific purpose of recovering passwords. They still do orders of magnitude better than CPU’s, but if one’s looking for a solution that prioritizes absolute performance over price/performance, there are alternatives.

 How Would You Like Your Eggs?
A single top of the line video card such as AMD Radeon 7970 consumes about 300 W at top load. It generates so much heat you can literally fry an egg on it! A cluster of four gaming video cards installed into a single PC will suck power and generate so much heat that cooling becomes a serious issue.

Accelerating Password Recovery with FPGAs
High-performance password cracking can be achieved with other devices. Field Programmable Gate Arrays (FPGAs) will fit the bill just perfectly. A single 4U chassis with a cluster of FPGA’s installed can offer a computational equivalent of over 2,000 dual-core processors.

The power consumption of FPGA-based units is dramatically less than that of consumer video cards. For example, units such as Pico E-101 draw measly 2.5 W. FPGA-based solutions don’t even approach the level of power consumption and heat generation of gaming video cards, running much cooler and comprising a much more stable system.

GPU vs. FPGA Acceleration: The Battle
Both GPU and FPGA acceleration approaches have their pros and contras. The GPU approach offers the best value, delivering optimal price/performance ratio to savvy consumers and occasional users. Heavy users will have to deal with increased power consumption and heat generation of GPU clusters.

FPGA’s definitely cost more per teraflop of performance. However, they are better optimized for applications such as password recovery (as opposed to 3D and video calculations), delivering significantly better performance – in absolute terms – compared to GPU-accelerated systems. FPGA-based systems generate much less heat than GPU clusters, and consume significantly less power. In addition, an FPGA-based system fits perfectly into a single 4U chassis, allowing forensic users building racks stuffed with FPGA-based systems. This is the very reason why many government, intelligence, military and law enforcement agencies are choosing FPGA-based systems.