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ÐMuch emphasis is now placed on chip-multiprocessor (CMP) architectures for exploiting thread-level parallelism in an application. In such architectures, speculation may be employed to execute applications that cannot be parallelized statically. In this paper, we present an efficient CMP architecture for speculative execution of sequential binaries without source recompilation. We present the software support that enables identification of threads from a sequential binary. The hardware includes a memory disambiguation mechanism that enables the detection of interthread memory dependence violations during speculative execution. This hardware is different from past proposals in that it does not rely on a snoopy-based cache-coherence protocol. Instead, it uses an approach similar to a directory-based scheme. Furthermore, the architecture includes a simple and efficient hardware mechanism to enable register-level communication between on-chip processors. Evaluation of this software-hardware approach shows that it is quite effective in achieving high performance when running sequential binaries.

Transactional Memory (TM), Thread-Level Speculation (TLS), and Checkpointed multiprocessors are three popular architectural techniques based on the execution of multiple, cooperating speculative threads. In these environments, correctly maintaining data dependences across threads requires mechanisms for disambiguating addresses across threads, invalidating stale cache state, and making committed state visible. These mechanisms are both conceptually involved and hard to implement. In this paper, we present Bulk, a novel approach to simplify these mechanisms. The idea is to hash-encode a thread's access information in a concise signature, and then support in hardware signature operations that efficiently process sets of addresses. Such operations implement the mechanisms described. Bulk operations are inexact but correct, and provide substantial conceptual and implementation simplicity. We evaluate Bulk in the context of TLS using SPECint2000 codes and TM using multithreaded Java workloads. Despite its simplicity, Bulk has competitive performance with more complex schemes. We also find that signature configuration is a key design parameter.

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Although adaptive processors can exploit application variability to improve performance or save energy, effectively managing their adaptivity is challenging. To address this problem, we introduce a new approach to adaptivity: the Positional approach. In this approach, both the testing of configurations and the application of the chosen configurations are associated with particular code sections. This is in contrast to the currently-used Temporal approach to adaptation, where both the testing and application of configurations are tied to successive intervals in time.We propose to use subroutines as the granularity of code sections in positional adaptation. Moreover, we design three implementations of subroutine-based positional adaptation that target energy reduction in three different workload environments: embedded or specialized server, general purpose, and highly dynamic. All three implementations of positional adaptation are much more effective than temporal schemes. On average, they boost the energy savings of applications by 50% and 84% over temporal schemes in two experiments.