Several Hybrid Transactional Memory (HyTM) schemes have recently been proposed to complement the fast, but best-effort, nature of Hardware Transactional Memory (HTM) with a slow, reliable software backup. However, the fundamental limitations of building a HyTM with nontrivial concurrency between

tend to be conservative in their security guarantees, typically adding 16–32 bytes of overhead. With small memories, weak processors, limited energy, and 30 byte packets, sensor networks cannot afford this luxury. TinySec addresses these extreme resource constraints with careful design; we explore

, and process migrations. If the transactional model is to gain wide acceptance, hardware support for transactions must be virtualized to hide these limitations in much the same way that virtual memory shields the programmer from platform-specific limitations of physical memory. This paper proposes Virtual

are considered too slow. Proposals for supporting “unbounded” transactions in hardware entail significantly higher complexity and risk than best-effort designs. We introduce Hybrid Transactional Memory (HyTM), an approach to implementing TM in software so that it can use best-effort hardware TM (HTM) to boost

using a dual itemset-tidset search tree, using an efficient hybrid search that skips many levels. It also uses a technique called diffsets to reduce the memory footprint of intermediate computations. Finally it uses a fast hash-based approach to remove any “non-closed” sets found during computation

, which is critical for their scalability, and the invisibility of read operations, which reduces memory contention. This paper proves an inherent tradeoff for implementations of transactional memories: they cannot be both disjointaccess parallel and have read-only transactions that are invisible

possibly unnecessary serialization, and possible deadlock. Transactional memory is an alternative mechanism that makes parallel programming easier. With transactional memory, a transaction provides atomic and serializable operations on an arbitrary set of memory locations. When a transaction commits, all

Abstract—Transactional Memory (TM) is emerging as a promising technology to simplify parallel programming. While several TM systems have been proposed in the research literature, we are still missing the tools and workloads necessary to analyze and compare the proposals. Most TM systems have been

contention. This paper proves an inherent tradeoff for implementations of transactional memories: they cannot be both disjoint-access parallel and have read-only transactions that are invisible and always terminate successfully. In fact, a lower bound of Ω(t) is proved on the number of writes needed in order

applications, such as on-line transaction processing (OLTP), which suffer from large memory stall times and exhibit little instruction-level parallelism. Given that commercial applications constitute by far the most important market for high-performance servers, the above trends emphasize the need to consider