Issue link: https://digital.copcomm.com/i/6960
As we all know, what took the place of those machines was a new generation of workstations and PCs —and at fi rst they might not have been capable of the same complex computing of the glass-house mainframes, but at least they belonged to their users and could pro- vide an answer when asked. It was well worth the sacrifi ce. IBM puts the birth of the PC at 1981; the Mac fi rst said "hello" in 1984. Time has passed, and the capabilities of desktop computers have actually surpassed that of those old gargantuan mainframe comput- ers, but high-end computing is no longer a monster computer in a glass house—it is thousands and thousands of processors in rows and rows in warehouses. At the recent Supercomputing Conference (SC09), the Cray Jaguar took the top spot in the TOP500 list of the world's fastest supercomputers. It is now based on six-core processors from ATI, has a total of 255,000 cores, and posted a 1.75-petafl op performance speed running Linpack. e Jaguar lives at the Oak Ridge Leadership Computing facility in Oak Ridge, Tennessee, and is put to work in climate science, chem- istry, materials science, nuclear energy, physics, bioenergy, astrophys- ics, geoscience, fusion, and combustion. In performance, the Jaguar competes closely with an IBM Road- runner computer at Los Alamos in New Mexico, the former fastest computer. e Roadrunner has 6562 dual-core AMD Opterons and 12,240 Cell processors from IBM. And, the list goes on. In all, there are millions of processors hard at work in the TOP500 computers, and there is another generation of priests serving these beasts. e beat goes on, and enormous change is coming to the compute world. In a way, it's a repeat of that last revolution. What happens when you have a supercomputer at your desk? Well, they are already here. Nvidia has its Tesla, a computer on an add-in board that takes advantage of the many cores in a GPU. e numbers now range from 128, 240, and 512 for the new Fermi. And, with this processor, Nvidia has turned its focus on high-performance computing (HPC), develop- ing fi rst for this market, and addressing the mainstream market next with a variant (at least that's how it looks from here at the moment). AMD can off er a 400-, 800-, or 1600-core ATI FireStream board. Dell and Cray Computer at SC09 showcased the Cray CX1- iWS deskside computer, which combines a visualization cluster us- ing Nvidia processors with eight-core Xeon processors in a compute cluster. Several independent software vendors (ISVs) have already an- nounced support for the new machine, including Dassault and Ansys for their analysis tools and e MathWorks for MatLab, its scientifi c and engineering software. At the moment, there is fi erce competition in the realm of HPC as the leading computer scientists and processor makers hash out the various approaches to solving big problems. e stakes are high. e strategies developed to drive giant super computers are also going to go to work on mainstream problems as well, for video transcoding, rendering, physics, imaging fi lters, and image enhancement. And the list will grow, so this is technology that will be in every computer down the road, and it's not a long road, either. ere are three basic paths being pursued by the processor compa- nies. Intel is championing the multi-CPU core approach. AMD is in there as well with multiple CPUs, but it is also pursuing Fusion, an integrated chip that includes CPUs and GPU cores. Nvidia and ATI, AMD's graphics subsidiary, are going for multiple GPUs, and at the moment, this approach—also referred to as heterogeneous comput- ing—has a great deal of traction. Rise of GPGPU GPGPU stands for general-purpose graphics processing unit, and the term is interchangeable with "GPU compute." GPU compute approaches take advantage of the hundreds of cores in a GPU to per- form tasks other than getting pixels to the screen. e trick is that you have to program applications in such a way that they behave like a graphics application. Nvidia has been very proactive in GPU com- pute, and the company has worked closely with university research centers to develop its CUDA tool for application development. e open standards body Khronos has developed OpenCL, a proj- ect that has involved Apple, AMD, and Nvidia, among other inter- Today, supercomputing is all about processors. At top is the Cray Jaguar, the world's fastest computer for open science; inset shows the Cray XT5 Kraken, the world's fastest academic supercomputer. February 2010 37 Computing ■ ■ ■ ■ Images ©Oak Ridge National Laboratory.