Data dependence speculation allows a compiler to relax the constraint of data-independence to issue tasks in parallel, increasing the potential for automatic extraction of parallelism from sequential programs. This paper proposes hardware mechanisms to support a data-dependence speculative distributed shared-memory (DDSM) architecture that enable speculative parallelization of programs with irregular data structures and inherent coarse-grain parallelism. Efficient support for coarse-grain tasks requires large buffers for speculative data; DDSM leverages cache and directory structures to provide large buffers that are managed transparently from applications. The proposed cache and directory extensions provide support for distributed speculat...
Speculative parallel execution of statically non-analyzable codes on Distributed Shared-Memory (DSM)...
Transactional memory systems promise to simplify parallel programming by avoiding deadlock, livelock...
Effectively utilizing available parallelism is becoming harder and harder as systems evolve to many-...
Maximal utilization of cores in multicore architectures is key to realize the potential performance ...
Run-time parallelization is often the only way to execute the code in parallel when data dependence ...
Thread-Level Data Speculation (TLDS) is a technique which enables the optimistic parallelization of ...
This work presents BMW, a new design for speculative implementations of memory consistency models in...
With speculative thread-level parallelization, codes that cannot be fully compiler-analyzed are aggr...
Thread-Level Data Speculation (TLDS) is a technique which enables the optimistic parallelization of ...
We present a software approach to design a thread-level data dependence speculation system targeting...
Dependences among loads and stores whose addresses are unknown hinder the extraction of instruction ...
The basic idea under speculative parallelization (also called thread-level spec-ulation) [2, 6, 7] i...
AbstractSpeculative software parallelism has gained renewed interest recently as a mechanism to leve...
grantor: University of TorontoTo fully exploit the potential of single-chip multiprocessor...
This work presents BMW, a new design for speculative implementations of memory consistency models in...
Speculative parallel execution of statically non-analyzable codes on Distributed Shared-Memory (DSM)...
Transactional memory systems promise to simplify parallel programming by avoiding deadlock, livelock...
Effectively utilizing available parallelism is becoming harder and harder as systems evolve to many-...
Maximal utilization of cores in multicore architectures is key to realize the potential performance ...
Run-time parallelization is often the only way to execute the code in parallel when data dependence ...
Thread-Level Data Speculation (TLDS) is a technique which enables the optimistic parallelization of ...
This work presents BMW, a new design for speculative implementations of memory consistency models in...
With speculative thread-level parallelization, codes that cannot be fully compiler-analyzed are aggr...
Thread-Level Data Speculation (TLDS) is a technique which enables the optimistic parallelization of ...
We present a software approach to design a thread-level data dependence speculation system targeting...
Dependences among loads and stores whose addresses are unknown hinder the extraction of instruction ...
The basic idea under speculative parallelization (also called thread-level spec-ulation) [2, 6, 7] i...
AbstractSpeculative software parallelism has gained renewed interest recently as a mechanism to leve...
grantor: University of TorontoTo fully exploit the potential of single-chip multiprocessor...
This work presents BMW, a new design for speculative implementations of memory consistency models in...
Speculative parallel execution of statically non-analyzable codes on Distributed Shared-Memory (DSM)...
Transactional memory systems promise to simplify parallel programming by avoiding deadlock, livelock...
Effectively utilizing available parallelism is becoming harder and harder as systems evolve to many-...