Remix: online detection and repair of cache contention for the JVM

Eizenberg, Ariel; Hu, Shiliang; Pokam, Gilles; Devietti, Joseph

doi:10.1145/2908080.2908090

Cited by 22 publications

(6 citation statements)

References 27 publications

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“…Lau et al [33] present a technique that allows a VM to determine whether an optimization improved or degraded by measuring CPU cycles. Remix [18] employs PMU to identify inter-thread false sharing on the fly. JXPerf [51] detects redundant memory operations by using PMU to sample memory locations accessed by a program and using debug registers to monitor subsequent accesses to the same location.…”

Section: Hardware Approachesmentioning

confidence: 99%

OJXPerf: Featherlight Object Replica Detection for Java Programs

Li,

Xu,

Zhao

et al. 2022

Preprint

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Memory bloat is an important source of inefficiency in complex production software, especially in software written in managed languages such as Java. Prior approaches to this problem have focused on identifying objects that outlive their life span. Few studies have, however, looked into whether and to what extent myriad objects of the same type are identical. A quantitative assessment of identical objects with code-level attribution can assist developers in refactoring code to eliminate object bloat, and favor reuse of existing object(s). The result is reduced memory pressure, reduced allocation and garbage collection, enhanced data locality, and reduced re-computation, all of which result in superior performance.We develop OJXPerf, a lightweight sampling-based profiler, which probabilistically identifies identical objects. OJXPerf employs hardware performance monitoring units (PMU) in conjunction with hardware debug registers to sample and compare field values of different objects of the same type allocated at the same calling context but potentially accessed at different program points. The result is a lightweight measurement -a combination of object allocation contexts and usage contexts ordered by duplication frequency. This class of duplicated objects is relatively easier to optimize. OJXPerf incurs 9% runtime and 6% memory overheads on average. We empirically show the benefit of OJXPerf by using its profiles to instruct us to optimize a number of Java programs, including well-known benchmarks and real-world applications. The results show a noticeable reduction in memory usage (up to 11%) and a significant speedup (up to 25%).

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Section: Hardware Approachesmentioning

confidence: 99%

OJXPerf: Featherlight Object Replica Detection for Java Programs

Li,

Xu,

Zhao

et al. 2022

Preprint

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“…Gulwani et al [19] proposed an automated program repair algorithm to use the existing correct student solutions to provide feedback for incorrect ones in programming education. Remix [16] leverages Intel's performance counter techniques to detect and repair false sharing bugs in multithreaded programs. Huron [26] presents a hybrid false sharing and repair framework with a low overhead.…”

Section: Related Workmentioning

confidence: 99%

HangFix

Dai²,

et al. 2020

Proceedings of the 11th ACM Symposium on Cloud Computing

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Software hang bugs are notoriously difficult to debug, which often cause serious service outages in cloud systems. In this paper, we present HangFix, a software hang bug fixing framework which can automatically fix a hang bug that is triggered and detected in production cloud environments. Hang-Fix first leverages stack trace analysis to localize the hang function and then performs root cause pattern matching to classify hang bugs into different types based on likely root causes. Next, HangFix generates effective code patches based on the identified root cause patterns. We have implemented a prototype of HangFix and evaluated the system on 42 real-world software hang bugs in 10 commonly used cloud server applications. Our results show that HangFix can successfully fix 40 out of 42 hang bugs in seconds. CCS CONCEPTS • Computer systems organization → Reliability; Availability; Cloud computing; • Software and its engineering → Software performance; Software testing and debugging.

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“…Remix [14], similar to JXPerf, also utilized PMU; while JXPerf identifies intra-thread inefficiencies, such as redundant/useless operations, Remix dentifies false sharing across threads.…”

Section: Related Workmentioning

confidence: 99%

Pinpointing performance inefficiencies in Java

Wang

Chabbi³

et al. 2019

Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of

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Many performance inefficiencies such as inappropriate choice of algorithms or data structures, developers' inattention to performance, and missed compiler optimizations show up as wasteful memory operations. Wasteful memory operations are those that produce/consume data to/from memory that may have been avoided. We present, JXPerf, a lightweight performance analysis tool for pinpointing wasteful memory operations in Java programs. Traditional byte-code instrumentation for such analysis (1) introduces prohibitive overheads and (2) misses inefficiencies in machine code generation. JXPerf overcomes both of these problems. JXPerf uses hardware performance monitoring units to sample memory locations accessed by a program and uses hardware debug registers to monitor subsequent accesses to the same memory. The result is a lightweight measurement at machine-code level with attribution of inefficiencies to their provenance -machine and source code within full calling contexts. JXPerf introduces only 7% runtime overhead and 7% memory overhead making it useful in production. Guided by JXPerf, we optimize several Java applications by improving code generation and choosing superior data structures and algorithms, which yield significant speedups. CCS CONCEPTS• General and reference → Metrics; Performance; • Software and its engineering → Software maintenance tools. 142 for ( int bit = 0, dual = 1; bit < logn ; bit ++ , dual *= 2) { 143 ... 144 for ( int a = 1; a < dual ; a ++) { 145 ... 146 for ( int b = 0; b < n; b += 2* dual ) { 147 int i = 2* b ; 148 int j = 2*( b + dual ); 149 double z1_real = data [j ]; 150 double z1_imag = data [j +1]; 151 double wd_real = w_real * z1_real -w_imag * z1_imag ; 152 double wd_imag = w_real * z1_imag + w_imag * z1_real ; 153 ▶ data [j] = data [i] -wd_real ; 154 data [j +1] = data [i +1] -wd_imag ; 155 ▶ data [i] += wd_real ; 156 data [i +1] += wd_imag ; 157 }}} Listing 1: Redundant memory loads in SPECjvm 2008 scimark.fft. data[i]is loaded from memory twice in a single iteration whereas it is unmodified between these two loads.

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Remix: online detection and repair of cache contention for the JVM

Cited by 22 publications

References 27 publications

OJXPerf: Featherlight Object Replica Detection for Java Programs

OJXPerf: Featherlight Object Replica Detection for Java Programs

HangFix

Pinpointing performance inefficiencies in Java

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