GreenMalloc: Allocator Optimisation for Industrial Workloads
For developers of memory-intensive applications, this provides an automated way to optimize allocator parameters, though the gains are modest and the approach is incremental.
GreenMalloc automatically configures memory allocators using multi-objective search, achieving up to 4.1% reduction in heap usage without runtime loss (0.25% reduction) across diverse workloads.
We present GreenMalloc, a multi objective search-based framework for automatically configuring memory allocators. Our approach uses NSGA II and rand_malloc as a lightweight proxy benchmarking tool. We efficiently explore allocator parameters from execution traces and transfer the best configurations to gem5, a large system simulator, in a case study on two allocators: the GNU C/CPP compiler's glibc malloc and Google's TCMalloc. Across diverse workloads, our empirical results show up to 4.1 percantage reduction in average heap usage without loss of runtime efficiency; indeed, we get a 0.25 percantage reduction.