With the emergence of multicore processors, various aggressive execution models have been proposed to exploit fine-grained thread-level parallelism, taking advantage of the fast on-chip interconnection communication. However, the aggressive nature of these execution models often leads to excessive energy consumption incommensurate to execution time reduction. In the context of Thread-Level Speculation, we demonstrated that on a same-ISA heterogeneous multicore system, by dynamically deciding how on-chip resources are utilized, speculative threads can achieve performance gain in an energy-efficient way.Through a systematic design space exploration, we built a multicore architecture that integrates heterogeneous components of processing cores and first-level caches. To cope with processor reconfiguration overheads, we introduced runtime mechanisms to mitigate their impacts. To match program execution with the most energy-efficient processor configuration, the system was equipped with a dynamic resource allocation scheme that characterizes program behaviors using novel processor counters.We evaluated the proposed heterogeneous system with a diverse set of benchmark programs from SPEC CPU2000 and CPU20006 suites. Compared to the most efficient homogeneous TLS implementation, we achieved similar performance but consumed 18% less energy. Compared to the most efficient homogeneous uniprocessor running sequential programs, we improved performance by 29% and reduced energy consumption by 3.6%, which is a 42% improvement in energy-delay-squared product.