GPU workloads with large memory footprints frequently suffer from redundant L2 TLB misses in which a recently evicted translation is immediately re-walked at full page-walk cost. We characterize these dead-entry misses across 24 GPU workloads, finding they account for up to 99% of L2 TLB misses in the most TLB-sensitive applications, yet their performance impact varies widely depending on memory access structure. Workloads where warps share the same virtual page suffer from burst amplification, where a single eviction stalls many warps simultaneously waiting for one translation to return. In contrast, workloads where each warp accesses a distinct set of pages face a capacity-overflow problem that no replacement policy can resolve, a distinction validated by huge page experiments. Building on this two-class taxonomy, we design DEPOT (Dead-Entry PrOTection), a 1 KB Bloom filter mechanism that prevents recently evicted translations from being displaced immediately upon reinstallation, delivering up to 72% IPC improvement on interference-driven workloads with zero overhead on others, and composing with the state-of-the-art TLB prefetching and compaction mechanism, for 2 to 7% additional gain.

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