Could updated analog computer technology – popular from about 1940-1970 –be developed to build high-speed CPUs for certain specialized applications?
Researchers at the Defense Advanced Research Projects Agency are looking to discover -- through a program called Analog and Continuous-variable Co-processors for Efficient Scientific Simulation (ACCESS) -- what advances analog computers might have over today’s supercomputers for a large variety of specialized applications such as fluid dynamics or plasma physics.
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“[Analog computers and] their potential to excel at dynamical problems too challenging for today’s digital processors may today be bolstered by other recent breakthroughs, including advances in micro-electromechanical systems, optical engineering, microfluidics, metamaterials and even approaches to using DNA as a computational platform. It is conceivable, Tang that novel computational substrates could exceed the performance of modern CPUs for certain specialized problems, if they can be scaled and integrated into modern computer architectures,” said Vincent Tang, program manager in DARPA’s Defense Sciences Office in a statement.
“Critical equations, known as partial differential equations, describe fundamental physical principles like motion, diffusion, and equilibrium. But because they involve continuous rates of change over a large range of physical parameters relating to the problems of interest—and in many cases also involve long-distance interactions—they do not lend themselves to being broken up and solved in discrete pieces by individual CPUs. A processor specially designed for such equations may enable revolutionary new simulation capabilities for design, prediction, and discovery. But what might that processor look like?”
DARPA recently issued a Request For Information soliciting the industry for details on how such analog or hybrid analog computer systems might work. The RFI is requesting responses in four interrelated Technical Areas as DARPA calls them. These include
- Scalable, controllable, and measurable processes that can be physically instantiated in co-processors for acceleration of computational tasks frequently encountered in scientific simulation
- Algorithms that use analog, non-linear, non-serial, or continuous-variable computational primitives to reduce the time, space, and communicative complexity relative to von Neumann/CPU/GPU processing architectures
- System architectures, schedulers, hybrid and specialized integrated circuits, compute languages, programming models, controller designs, and other elements for efficient problem decomposition, memory access, and task allocation across multi-hybrid co-processors
- Methods for modeling and simulation via direct physical analogy
Analog computers solve equations by manipulating continuously changing values instead of discrete measurements. In their prime most analog computers were designed for specific applications, like heavy-duty math or flight component simulation. “In the 1930s, for example, Vannevar Bush—who a decade later would help initiate and administer the Manhattan Project—created an analog “differential analyzer” that computed complex integrations through the use of a novel wheel-and-disc mechanism. And in the 1940s, the Norden bombsight made its way into U.S. warplanes, where it used analog methods to calculate bomb trajectories,” DARPA noted.
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