Cryptography algorithms that take longer to solve on a GPU than a CPU I know that Graphics cards are faster at solving algorithms like SHA-256 because of the many builtin processors, but are there Algorithms that take actually longer on a Graphics card than on a modern consumer CPU (Amd/intel)?
This specific situation is a central part of the analysis of password hashing functions. Indeed, for hashing a password, we want a function which is:


slow in a tunable way;
such that the most cost-effective hardware for evaluating many instances of the function is the hardware that the expected defender will use, i.e. a "normal PC".


"Cost" here means actual money. For the attacker, it does not matter whether he will need 10, 100 or 1000 units of whatever hardware he'll use; only the total cost will be necessary. It can be argued that with modern hardware, in particular GPU, the majority of the budget for crunching passwords will be spent on electrical power, not on purchasing the hardware. Therefore, it makes sense to define the cost of the function with regards to the energy consumed by its computation, on both general-purpose CPU, and various GPU.

The bcrypt password hashing function appears to be indeed such a function, that is more expensive (energy-wise) to compute on a GPU than on a CPU. The bcrypt feature that makes it so is that it is organized around an internal 4 kB array of data which is continuously read and modified in a way which is not amenable to shortcuts, and at pseudorandom addresses. GPU are not well-equipped for that; if you try to implement bcrypt on a GPU, you will experience considerable contention for data access, and most of the GPU cores will be stalled at any time (and such a stalled core still consumes power).

The Password Hashing Competition was organized to define new functions that fulfill a larger goal, namely to not only be more CPU-friendly than GPU-friendly, but also to "hold the line" to some extent when facing attackers with FPGA or custom ASIC. The main tool used by most candidates was again RAM, but more of it; the underlying assumption is that modern PC (servers, desktop systems...) contain a thoroughly optimized memory bus that cannot be operated at a substantially lower cost by custom hardware. It is unclear how far that assumption holds.

One of the PHC candidates, called Makwa (which I designed), did not use RAM but modular arithmetics. This is not expected to fare well against FPGA and ASIC, but, for GPU, it appears to behave well: according to my analysis, costs on CPU and GPU appear to be roughly on par for a 2048-bit modulus, and larger moduli benefit the CPU more than the GPU.

To sum up, both bcrypt and Makwa seem to be valid answers to your question, and they do so through quite different means.