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F. Castro

Publications and source records attributed to F. Castro.

3 recordsLinked to original sources

Teaching Experiences using the RVfpga Package

The RVfpga course offers a solid introduction to computer architecture using the RISC-V instruction set and FPGA technology. It focuses on providing hands-on experience with real-world RISC-V cores, the VeeR EH1 and the VeeR EL2, developed by Western Digital a few years ago and currently hosted by ChipsAlliance. This course is particularly aimed at educators and students in computer science, computer engineering, and related fields, enabling them to integrate practical RISC-V knowledge into their curricula. The course materials, which include detailed labs and setup guides, are available for free through the Imagination University Programme website. We have used RVfpga in different teaching activities and we plan to continue using it in the future. Specifically, we have used RVfpga as the main experimental platform in several bachelor/master degree courses; we have completed several final bachelor/master degree projects based on this platform; we will conduct a microcredential about processor design based on RVfpga; we have adapted RVfpga to a MOOC in the edX platform; and we have shared RVfpga worldwide through one-day hands-on workshops and tutorials. This paper begins by discussing how the RVfpga course matches the latest IEEE/ACM/AAAI computing curriculum guidelines. It then details various teaching implementations we have conducted over recent years using these materials. Finally, the paper examines other courses similar to RVfpga, comparing their strengths and weaknesses.

cs.AR

Exact cost minimization of a series-parallel system

The redundancy allocation problem is formulated minimizing the design cost for a series-parallel system with multiple component choices whereas ensuring a given system reliability level. The obtained model is a nonlinear integer programming problem with a non linear, non separable constraint. We propose an algebraic method, based on Gr\"obner bases, to obtain the exact solution of the problem. In addition, we provide a closed form for the required Gr\"obner bases, avoiding the bottleneck associated with the computation, and promising computational results.

math.OC

An algebraic approach to Integer Portfolio problems

Integer variables allow the treatment of some portfolio optimization problems in a more realistic way and introduce the possibility of adding some natural features to the model. We propose an algebraic approach to maximize the expected return under a given admissible level of risk measured by the covariance matrix. To reach an optimal portfolio it is an essential ingredient the computation of different test sets (via Gröbner basis) of linear subproblems that are used in a dual search strategy.

math.OC