I saw a good talk by Chris Baker at SIAM about multiprecision solvers, and was suitably embarrassed that we cannot do this. I still strongly believe that templates are the wrong solution, and mucking up perfectly good interfaces with a bunch of types we do not care about is wrong. I now have a proposal, outlined below. We start with the idea of a solver with a certain precision, so that each solver can report the precision it computes in. Let's restrict ourselves to solvers that only do simple vector operations for the time being. For this then, we need a Vec object which stores values and computes with this precision, which will be discussed below. Upon entering, we call VecConvert() on the input vector to get the correct precision, which just references the object if no conversion is necessary. We VecConvert() the output vector as well before filling it, and the VecConvert() to the output on the way out. If not conversion is necessary, we get the ssme pointer for the first convert, and no-op for the second. All internal vectors are created with the solver precision. This all depends on having Vec objects of different precisions. I propose we have a different Vec implementation for each precision, maybe saving code by having configure or make generate the different precisions from a single template. Most Vec operations work by first calling VecGetArray() and then some BLAS calls. I would now have VecGetArray() do copy-in/copy-out if internal storage has a different precision than PetscScalar, and add the function VecGetArrayPrecise(Vec v, PetscDataType precision, void **array) which returns the internal storage if it is the correct precision, and fails otherwise. If we switch implementations to VecGetArrayPrecise(), then vectors will work with other vectors of the same precision and fail otherwise. I think this is the correct level of sanity with multi-precision code (demand explicit conversions of dissimilar types). I am only really interested in trying this with float+double (Chris spent all of his time on qd128 which I think has no real scientific relevance, but of course we will do this too). The code changes are relatively minor: - Add a precision (PetscDataType) to Vec - One new Vec method, VecGetArrayPrecise() - Make VecDuplicate() respect precision - New Vec implementation for float, built from a template by Python If we give a float Vec to Picard, it should compute everything in float since the Vecs are duplicated. We can add the solver convert code later if everything works as expected. I think the first interesting test would be a nonlinear float preconditioner for a double SNES. I am not interested in being able to use whatever type I want everywhere. That will never work, and its not clear there is any benefit anyway. What I want is just to have solvers of different precisions work together with explicit conversion at the boundary. Why will this not work? If it will, why will it not be as easy as stated above? Matt -- What most experimenters take for granted before they begin their experiments is infinitely more interesting than any results to which their experiments lead. -- Norbert Wiener