Future microprocessors will have more serious memory wall problems since they will include more cores and threads in each chip. Similarly, future applications will have more serious memory bloat problems since they are more often written using object-oriented languages and reusable frameworks. To overcome such problems, the language runtime environments must accurately and efficiently profile how programs access objects. We propose Barrier Profiler, a low-overhead object access profiler using a memory-protection-based approach called pointer barrierization and adaptive overhead reduction techniques. Unlike previous memory-protection-based techniques, pointer barrierization offers per-object protection by converting all of the pointers to a given object to corresponding barrier pointers that point to protected pages. Barrier Profiler achieves low overhead by not causing signals at object accesses that are unrelated to the needed profiles, based on profile feedback and a compiler analysis. Our experimental results showed Barrier Profiler provided sufficiently accurate profiles with 1.3% on average and at most 3.4% performance overhead for allocation-intensive benchmarks, while previous code-instrumentation-based techniques suffered from 9.2% on average and at most 12.6% overhead. The low overhead allows Barrier Profiler to be run continuously on production systems. Using Barrier Profiler, we implemented two new online optimizations to compress write-only character arrays and to adjust the initial sizes of mostly non-accessed arrays. They resulted in speed-ups of up to 8.6% and 36%, respectively. © 2012 ACM.