Ziruox worked on GPU performance optimizations for multitoken attention in the mirage-project/mirage repository, focusing on accelerating attention computations by loading paged key-value indices into shared memory. Using C++ and CUDA, Ziruox implemented targeted memory optimizations and refined kernel scheduling to improve throughput for multitoken workloads. The work addressed the challenge of efficiently handling large-scale attention mechanisms on GPUs, aligning with the repository’s performance goals. Although the contribution spanned one feature over a month, the technical depth involved parallel computing concepts and careful integration into the existing codebase, resulting in measurable throughput improvements for multitoken attention tasks on modern hardware.