CVXGEN generates fast custom code for small, QP-representable convex optimization problems, using an online interface with no software installation. With minimal effort, turn a mathematical problem description into a high speed solver.
Using CVXGENDescribe your LP or convex QP
Describe your small, quadratic program (QP) representable problem with a simple, powerful language.
Automatically generate a custom solver
CVXGEN automatically creates library-free C code for a custom, high-speed solver. This can be downloaded and used immediately, and requires nothing but a C compiler. CVXGEN also supplies a Matlab function that, with one command, downloads and builds a custom Matlab mex solver.
Solve your problems up to 10,000 times faster
CVXGEN performs most transformations and optimizations offline, to make online solution as fast as possible. Code generation takes a few seconds or minutes, producing solvers that work in microseconds or milliseconds. Compared with CVX, solution times are typically at least 20 times faster, with the smallest problems showing speedup as large as 10,000×.
CVXGEN is for convex, QP-representable problems only. It works best for small problems, where the final system has around 2000 total coefficients in the constraints and objective. CVXGEN does not work well for larger problems.
AuthorsJacob Mattingley, a Ph.D. candidate at Stanford University (primary author)
Stephen Boyd, a professor at Stanford University (advisor)
CVXGEN: A Code Generator for Embedded Convex Optimization, J. Mattingley and S. Boyd, Working manuscript, November 2010
Code Generation for Receding Horizon Control, J. Mattingley, Y. Wang and S. Boyd, Working manuscript, August 2010
Real-Time Convex Optimization in Signal Processing, J. Mattingley and S. Boyd, IEEE Signal Processing Magazine, 27(3):50-61, May 2010
Automatic Code Generation for Real-Time Convex Optimization, J. Mattingley and S. Boyd, chapter in Convex Optimization in Signal Processing and Communications, Y. Eldar and D. Palomar, Eds., Cambridge University Press, 2009
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