[R-SIG-Finance] Basic Mean Variance Optimization

[burke nersesian]

Need single period weighting for simple portfolio (minimal assumptions and constraints).
Each asset has a variance = 1.0 and expected return = 1.0 and the covariance with each of the other assets in the portfolio is > 0.0 and < 1.0,
(in other words, the weighting will only be dependent on the covariance matrix to produce in essence the minimum variance portfolio). 
If possible, I would prefer each weight to be positive. The portfolio contains hundreds of assets and must be calculated thousands of times so R seems too slow for the job.
Does anyone know of any C function in say, GSL, BLAS or any other library that takes a Convariance Matrix as input and returns a weight vector as output?
The solution doesn't have to be guaranteed to be robust, if it dominates the equal weighted portfolio that's sufficient.
Any ideas will help, thank you all so much!