Continuous object access profiling and optimizations to overcome the memory wall and bloat

Abstract

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 objectoriented 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.

YA-JOP:Yet Another Java Object Profiler On Art Virtual Machine

“…There are researches to steal bits in object header or change the layout of the object while recording object information [2,9,18] , such as access events, allocation site. Programs in the ART virtual machine have limited resources.…”

“…Other researchers have implemented tools to profile Android system and applications in IO overhead [7] , privacy leak [1] , application behaviour [14] , resource leak [19] , energy consumption [3] , etc. There are many researches and tools in other platform to track information of Java objects [2,4,6,8,9,10,13,16,17] . But these tools are not designed for the ART virtual machine and not available in Android platform.…”

JITProf: pinpointing JIT-unfriendly JavaScript code

“…Recent work includes tracebased dynamic type specialization [13], optimizing the representation of arrays based on object access profiles [30], memoizing side effect-free methods [42], identifying and removing short-lived objects [34], just-in-time value specialization [8], and studying how the effectiveness of JIT compilation depends on the order in which compilation units are (re)-compiled [11]. Hackett et al [17] improve the performance of the Firefox JavaScript engine through combined static-dynamic type inference that enables the engine to omit unnecessary runtime checks, given that the program matches particular regularity assumptions.…”