LASER: Light, Accurate Sharing dEtection and Repair


Contention for shared memory, in the forms of true sharing and false sharing, is a challenging performance bug to discover and to repair. Understanding cache contention requires global knowledge of the program's actual sharing behavior, and can even arise invisibly in the program due to the opaque decisions of the memory allocator. Previous schemes have focused only on false sharing, and impose significant performance penalties or require non-trivial alterations to the operating system or runtime system environment. This paper presents the Light, Accurate Sharing dEtection and Repair (LASER) system, which leverages new performance counter capabilities available on Intel's Haswell architecture that identify the source of expensive cache coherence events. Using records of these events generated by the hardware, we build a system for online contention detection and repair that operates with low performance overhead and does not require any invasive program, compiler or operating system changes. Our experiments show that LASER imposes just 2% average runtime overhead on the Phoenix, Parsec and Splash2x benchmarks. LASER can automatically improve the performance of programs by up to 19% on commodity hardware.

In proceedings of the 22nd International Symposium on High Performance Computer Architecture (Acceptance rate: 53/240 = 22%)
Akshitha Sriraman
Akshitha Sriraman
Assistant Professor

I am an Assistant Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University. My research bridges computer architecture and software systems, with a focus on making hyperscale data center systems more efficient (via solutions that span the systems stack). The central theme of my work is to (1) design software that is aware of new hardware constraints and (2) architect hardware that efficiently supports new hyperscale software requirements.