We propose a new semantics for shared-memory parallel programs that gives strong guarantees even in the presence of data races. Our local data race freedom property guarantees that all data-race-free portions of programs exhibit sequential semantics. We provide a straightforward operational semantics and an equivalent axiomatic model, and evaluate an implementation for the OCaml programming language. Our evaluation demonstrates that it is possible to balance a comprehensible memory model with a reasonable (no overhead on x86,~0.6% on ARM) sequential performance trade-off in a mainstream programming language.

User-facing online services utilize geo-distributed data stores to minimize latency and tolerate partial failures, with the intention of providing a fast, always-on experience. However, geo-distribution does not come for free; application developers have to contend with weak consistency behaviors, and the lack of abstractions to composably construct high-level replicated data types, necessitating the need for complex application logic and invariably exposing inconsistencies to the user. Some commercial distributed data stores and several academic proposals provide a lattice of consistency levels, with stronger consistency guarantees incurring increased latency and throughput costs. However, correctly assigning the right consistency level for an operation requires subtle reasoning and is often an error-prone task. In this paper, we present QUELEA, a declarative programming model for eventually consistent data stores (ECDS), equipped with a contract language, capable of specifying fine-grained applicationlevel consistency properties. A contract enforcement system analyses contracts, and automatically generates the appropriate consistency protocol for the method protected by the contract. We describe an implementation of QUELEA on top of an off-the-shelf ECDS that provides support for coordination-free transactions. Several benchmarks including two large web applications, illustrate the effectiveness of our approach.

Managed languages typically use read barriers to interpret forwarding pointers introduced to keep track of copied objects. For example, in a multicore environment with thread-local heaps and a global, shared heap, an object initially allocated on a local heap may be copied to a shared heap if it becomes the source of a store operation whose target location resides on the shared heap. As part of the copy operation, a forwarding pointer may be established in the original object to point to the copied object. This level of indirection avoids the need to update all of the references to the object that has been copied.In this paper, we consider the design of a managed runtime that eliminates read barriers. Our design is premised on the availability of a sufficient degree of concurrency to stall operations that would otherwise necessitate the copy. Stalled actions are deferred until the next local collection, avoiding exposing forwarding pointers to the mutator. In certain important cases, procrastination is unnecessary -lightweight runtime techniques can sometimes be used to allow objects to be eagerly copied when their set of incoming references is known, or when it can be determined that having multiple copies would not violate program semantics.We evaluate our techniques on 3 platforms: a 16-core AMD64 machine, a 48-core Intel SCC, and an 864-core Azul Vega 3. Experimental results over a range of parallel benchmarks indicate that our approach leads to notable performance gains (20 -32% on average) without incurring any additional complexity.