Force claims the Condor Cluster would be the 33rd largest supercomputer in the world in terms of capacity. The lab has opened up the supercomputer for use by universities for research. Distributed computing With the help of the computing power of over half a million PlayStation 3 consoles, the distributed computing project Folding@home has been recognized by Guinness World Records as the most powerful distributed network in the world. The first record was achieved on September 16, 2007, as the project surpassed one petaFLOPS, which had never previously been attained by a distributed computing network. Additionally, the collective efforts enabled PS3 alone to reach the petaFLOPS mark on September 23, 2007. In comparison, the world's second-most powerful supercomputer at the time, IBM's BlueGene/L, performed at around 478.2 teraFLOPS, which means Folding@home's computing power is approximately twice BlueGene/L's (although the CPU interconnect in BlueGene/L is more than one million times faster than the mean network speed in Folding@home). As of May 7, 2011, Folding@home runs at about 9.3 x86 petaFLOPS, with 1.6 petaFLOPS generated by 26,000 active PS3s alone. Mainframes IBM announced on April 25, 2007, that it would begin integrating its Cell Broadband Engine Architecture microprocessors into the company's line of mainframes. This has led to a gameframe. Password cracking The architecture of the processor makes it better suited to hardware-assisted cryptographic brute force attack applications than conventional processors. Software engineering Due to the flexible nature of the Cell, there are several possibilities for the utilization of its resources, not limited to just different computing paradigms: Job queue The PPE maintains a job queue, schedules jobs in SPEs, and monitors progress. Each SPE runs a "mini kernel" whose role is to fetch a job, execute it, and synchronize with the PPE. Self-multitasking of SPEs The mini kernel and scheduling is distributed across the SPEs. Tasks are synchronized using mutexes or semaphores as in a conventional operating system. Ready-to-run tasks wait in a queue for an SPE to execute them. The SPEs use shared memory for all tasks in this configuration. Stream processing Each SPE runs a distinct program. Data comes from an input stream and is sent to SPEs. When an SPE has terminated the processing, the output data is sent to an output stream. This provides a flexible and powerful architecture for stream processing, and allows explicit scheduling for each SPE separately. Other processors are also able to perform