This paper advocates the use of a monitor-and-recover programming paradigm to enhance the reliability of software, and proposes an architectural design that allows software and hardware to cooperate in making this paradigm more efficient and easier to program.We propose that programmers write monitoring functions assuming simple sequential execution semantics. Our architecture speeds up the computation by executing the monitoring functions speculatively in parallel with the main computation. For recovery, programmers can define fine-grain transactions whose side effects, including all register modifications and memory writes, can either be committed or aborted under program control. Transactions are implemented efficiently by treating them as speculative threads.Our experimental results suggest that monitored execution is more amenable to parallelization than regular program execution. Code monitoring is sped up by a factor of 1.5 by exploiting single-thread instruction-level parallelism, and by an additional factor of 1.6 using thread-level speculation. This results in an overall improvement of 2.5 times and a sustained 5.4 instructions-per-cycle performance. A monitored execution that used to be 2.5 times slower executes with a degradation of only 12% when compared to the performance on the baseline machine. We also show that the concept of fine-grain transactional programming is useful in catching buffer overrun errors through a number of real-life examples.