This metric represents a fraction of cycles spent on handling first-level data TLB (or UTLB) misses. As with ordinary data caching, focus on improving data locality and reducing working-set size to reduce UTLB overhead. Additionally, consider using profile-guided optimization (PGO) to collocate frequently-used data on the same page. Try using larger page sizes for large amounts of frequently-used data. This metric does not include store TLB misses.

A significant proportion of cycles is being spent handling first-level data TLB misses. As with ordinary data caching, focus on improving data locality and reducing working-set size to reduce UTLB overhead. Additionally, consider using profile-guided optimization (PGO) to collocate frequently-used data on the same page. Try using larger page sizes for large amounts of frequently-used data.