Linear solvers and eigensolvers are the heart of HPC scientific applications. Among them, iterative projection methods are preferred to direct algorithms for large problems because of their lower memory usage, but they are prone to roundoff errors. Using an enhanced working precision inside the linear computing kernels mitigates this issue and accelerates convergence. Today, to go beyond 80 bits of precision, the only option is to use software libraries which are very slow. We introduce the VaRiable and extended Precision Accelerator (VRP), a RISC-V accelerator implemented on a System-on-Chip (SoC) using GF22FDX technology. The VRP supports Floating Point (FP) computations with a range of significand bits from 2 to 512. This accelerator delivers an average 19.25x application speedup compared to the well-known MPFR software library running on a 2400 MHz Intel Xeon processor. Additionally, extended precision facilitates the convergence of linear solvers for problems that would otherwise fail to converge and reduces energy-to-solution.