Details
Multithreading is similar in concept to preemptive multitasking but is implemented at the thread level of execution in modern superscalar processors.
Simultaneous multithreading (SMT) is one of the two main implementations of multithreading, the other form being temporal multithreading. In temporal multithreading, only one thread of instructions can execute in any given pipeline stage at a time. In simultaneous multithreading, instructions from more than one thread can be executing in any given pipeline stage at a time. This is done without great changes to the basic processor architecture: the main additions needed are the ability to fetch instructions from multiple threads in a cycle, and a larger register file to hold data from multiple threads. The number of concurrent threads can be decided by the chip designers, but practical restrictions on chip complexity have limited the number to two for most SMT implementations, though there have been as many as 8 threads per core in, for example, the UltraSPARC T2.
Because the technique is really an efficiency solution and there is inevitable increased conflict on shared resources, measuring or agreeing on the effectiveness of the solution can be difficult. However, measured energy efficiency of SMT with parallel native and managed workloads on historical 130 nm to 32 nm Intel SMT (Hyper-Threading) implementations found that in 45 nm and 32 nm implementations, SMT is extremely energy efficient, even with inorder Atom processors . In modern systems, SMT effectively exploits concurrency with very little additional dynamic power.
Some researchers have shown that the extra threads can be used to proactively seed a shared resource like a cache, to improve the performance of another single thread, and claim this shows that SMT is not just an efficiency solution. Others use SMT to provide redundant computation, for some level of error detection and recovery.
However, in most current cases, SMT is about hiding memory latency, increasing efficiency, and increasing throughput of computations per amount of hardware used.
Read more about this topic: Simultaneous Multithreading
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