Abstract-As x86-64 processors become the CPU of choice for the personal computer market, it becomes increasingly important to understand the performance we can expect by migrating applications from a 32-bit environment to a 64-bit environment. For applications that can effectively exploit a larger memory address space (e.g., commercial databases and digital content authoring tools), it is not surprising that x86-64 can provide a performance boost. However, for less-demanding desktop applications that can fit in a 32-bit address space, we would like to know if we can expect any performance benefits by moving to this platform. In this paper, we report on a range of performance characteristics for programs compiled for both 32 bits and 64 bits and run directly (32-bit binaries are run in compatibility mode 1 ; 64-bit binaries are run in 64-bit mode) on a single x86-64 based system. In this study we utilize the integer benchmarks from the newly released SPEC CPU2006 suite. We have observed that for the SPEC CPU2006 integer benchmarks, 64-bit mode offers a sizable performance advantage over 32-bit mode (7% on average). However, the advantages vary from benchmark to benchmark, and for a handful of programs, 64-bit mode is significantly slower than 32-bit mode (in this subset of benchmarks, performance is reduced by more than 16% when running in 64-bit mode.) We further analyze 5 benchmarks that exhibit significant differences in performance between these two modes. For this set of CPU2006 integer programs, we present a range of performance characteristics that illustrate the impact of moving to a 64-bit environment. Our results and analysis can be used by performance engineers and developers to better understand how to exploit the capabilities of the x86-64 architecture.
This is investigated in REF , where differences between 32-bit and 64-bit SPEC-benchmark applications are analysed.
Performance Characterization of SPEC CPU2006 Integer Benchmarks on x86-64 Architecture
2006 IEEE International Symposium on Workload Characterization
2006 IEEE International Symposium on Workload Characterization
Computer Science