We demonstrate that general-purpose memory allocation involving many threads on many cores can be done with high performance, multicore scalability, and low memory consumption. For this purpose, we have designed and implemented scalloc, a concurrent allocator that generally performs and scales in our experiments better than other allocators while using less memory, and is still competitive otherwise. The main ideas behind the design of scalloc are: uniform treatment of small and big objects through so-called virtual spans, efficiently and effectively reclaiming free memory through fast and scalable global data structures, and constant-time (modulo synchronization) allocation and deallocation operations that trade off memory reuse and spatial locality without being subject to false sharing.

We present ACDC-JS, an open-source JavaScript memory management benchmarking tool. ACDC-JS incorporates a heap model based on real web applications and may be configured to expose virtually any relevant performance characteristics of JavaScript memory management systems. ACDC-JS is based on ACDC, a benchmarking tool for C/C++ that models periodic allocation and deallocation behavior (AC) as well as persistent memory (DC). We identify important characteristics of JavaScript mutator behavior and propose a configurable heap model based on typical distributions of these characteristics as foundation for ACDC-JS. We describe heap analyses of 13 real web applications extending existing work on JavaScript behavior analysis. Our experimental results show that ACDC-JS enables performance benchmarking and debugging of state-of-the-art JavaScript virtual machines such as V8 and SpiderMonkey by exposing key aspects of their memory management performance.

We present ACDC, an open-source benchmark that may be configured to emulate explicit single- and multi-threaded memory allocation, sharing, access, and deallocation behavior to expose virtually any relevant allocator performance differences. ACDC mimics periodic memory allocation and deallocation (AC) as well as persistent memory (DC). Memory may be allocated thread-locally and shared among multiple threads to study multicore scalability and even false sharing. Memory may be deallocated by threads other than the allocating threads to study blowup memory fragmentation. Memory may be accessed and deallocated sequentially in allocation order or in tree-like traversals to expose allocator deficiencies in exploiting spatial locality. We demonstrate ACDC's capabilities with seven state-of-the-art allocators for C/C++ in an empirical study which also reveals interesting performance differences between the allocators.

We propose a new memory model called short-term memory for managing objects on the heap. In contrast to the traditional persistent memory model for heap management, objects in short-term memory expire after a finite amount of time, which makes deallocation unnecessary. Instead, expiration of objects may be extended, if necessary, by refreshing. We have developed a concurrent, incremental, and non-moving implementation of short-term memory for explicit refreshing called self-collecting mutators that is based on programmer-controlled time and integrated into state-of-the-art runtimes of three programming languages: C, Java, and Go. All memory management operations run in constant time without acquiring any locks modulo the underlying allocators. Our implementation does not require any additional heap management threads, hence the name. Expired objects may be collected anywhere between one at a time for maximal incrementality and all at once for maximal throughput and minimal memory consumption. The integrated systems are heap management hybrids with persistent memory as default and short-term memory as option. Our approach is fully backwards compatible. Legacy code runs without any modifications with negligible runtime overhead and constant per-object space overhead. Legacy code can be modified to take advantage of short-term memory by having some but not all objects allocated in short-term memory and managed by explicit refreshing. We study single- and multi-threaded use cases in all three languages macro-benchmarking C and Java and micro-benchmarking Go. Our results show that using short-term memory (1) simplifies heap management in a state-of-the-art H.264 encoder written in C without additional time and minor space overhead, and (2) improves, at the expense of safety, memory management throughput, latency, and space consumption by reducing the number of garbage collection runs, often even to zero, for a number of Java and Go programs.