Dynamic Helper Threaded Prefetching on the Sun UltraSPARC CMP Processor

Pre-execution techniques have received much attention as an effective way of prefetching cache blocks to tolerate the ever-increasing memory latency. A number of pre-execution techniques based on hardware, compiler, or both have been proposed and studied extensively by researchers. They report promising results on simulators that model a simultaneous multithreading (SMT) processor. We apply the helper threading idea on a real multithreaded machine, i.e., Intel Pentium 4 processor with hyper-threading technology, and show that indeed it can provide wall-clock speedup on real silicon. To achieve further performance improvements via helper threads, we investigate three helper threading scenarios that are driven by automated compiler infrastructure, and identify several key challenges and opportunities for novel hardware and software optimizations. Our study shows a program behavior changes dynamically during execution. In addition, the organizations of certain critical hardware structures in the hyper-threaded processors are either shared or partitioned in the multithreading mode and thus, the tradeoffs regarding resource contention can be intricate. Therefore, it is essential to judiciously invoke helper threads by adapting to the dynamic program behavior so that we can alleviate potential performance degradation due to resource contention. Moreover, since adapting to the dynamic behavior requires frequent thread synchronization, having light-weight thread synchronization mechanisms is important.

Pre-execution techniques have received much attention as an effective way of prefetching cache blocks to tolerate the ever-increasing memory latency. A number of pre-execution techniques based on hardware, compiler, or both have been proposed and studied extensively by researchers. They report promising results on simulators that model a simultaneous multithreading (SMT) processor. We apply the helper threading idea on a real multithreaded machine, i.e., Intel Pentium 4 processor with hyper-threading technology, and show that indeed it can provide wall-clock speedup on real silicon. To achieve further performance improvements via helper threads, we investigate three helper threading scenarios that are driven by automated compiler infrastructure, and identify several key challenges and opportunities for novel hardware and software optimizations. Our study shows a program behavior changes dynamically during execution. In addition, the organizations of certain critical hardware structures in the hyper-threaded processors are either shared or partitioned in the multithreading mode and thus, the tradeoffs regarding resource contention can be intricate. Therefore, it is essential to judiciously invoke helper threads by adapting to the dynamic program behavior so that we can alleviate potential performance degradation due to resource contention. Moreover, since adapting to the dynamic behavior requires frequent thread synchronization, having light-weight thread synchronization mechanisms is important.

Heterogeneous Many Cores (HMC) architectures that mix many simple/small cores with a few complex/large cores are emerging as a design alternative that can provide both fast sequential performance for single threaded workloads and power-efficient execution for through-put oriented parallel workloads. The availability of many small cores in a HMC presents an opportunity to utilize them as low-power helper cores to accelerate memory-intensive sequential programs mapped to a large core. However, the latency overhead of accessing small cores in a loosely coupled system limits their utility as helper cores. Also, it is not clear if small cores can execute helper threads sufficiently in advance to benefit applications running on a larger, much powerful, core. In this paper, we present a hardware/software framework called coretethering to support efficient helper threading on heterogeneous manycores. Core-tethering provides a co-processor like interface to the small cores that (a) enables a large core to directly initiate and control helper execution on the helper core and (b) allows efficient transfer of execution context between the cores, thereby reducing the performance overhead of accessing small cores for helper execution. Our evaluation on a set of memory intensive programs chosen from the standard benchmark suites show that, helper threads using moderately sized small cores can significantly accelerate a larger core compared to using a hardware prefacer alone. We find that a small core provides a good trade-off against using an equivalent large core to run helper threads in a HMC. Additionally, helper prefetching on small cores when used along with hardware prefetching, can provide an alternate design point to growing instruction window size for achieving higher sequential performance on memory intensive applications.

This paper presents a helper thread prefetching scheme that is designed to work on loosely-coupled processors, such as in a standard chip multiprocessor (CMP) system or an intelligent memory system. Loosely-coupled processors have an advantage in that fine-grain resources, such as processor and L1 cache resources, are not contended by the application and helper threads, hence preserving the speed of the application. However, inter-processor communication is expensive in such a system. We present techniques to alleviate this. Our approach exploits large loop-based code regions and is based on a new synchronization mechanism between the application and helper threads. This mechanism precisely controls how far ahead the execution of the helper thread can be with respect to the application thread. We found that this is important in ensuring prefetching timeliness and avoiding cache pollution. To demonstrate that prefetching in a loosely-coupled system can be done effectively, we evaluate our prefetching in a standard, unmodified CMP system, and in an intelligent memory system where a simple processor in memory executes the helper thread. Evaluating our scheme with nine memory-intensive applications with the memory processor in DRAM achieves an average speedup of 1.25. Moreover, our scheme works well in combination with a conventional processor-side sequential L1 prefetcher, resulting in an average speedup of 1.31. In a standard CMP, the scheme achieves an average speedup of 1.33.

Today's general-purpose processors are increasingly using multithreading in order to better leverage the additional on-chip real estate available with each technology generation. Simultaneous multi-threading (SMT) was originally proposed as a large dynamic superscalar processor with monolithic hardware structures shared among all threads. Inters hyper-threaded Pentium 4 processor partitions the queue structures among two threads, demonstrating more balanced performance by reducing the hoarding of structures by a single thread. IBM's Power5 processor is a 2-way chip multiprocessor (CMP) of SMT processors, each supporting 2 threads, which significantly reduces design complexity and can improve power efficiency. This paper examines processor partitioning options for larger numbers of threads on a chip. While growing transistor budgets permit four and eight-thread processors to be designed, design complexity, power dissipation, and wire scaling limitations create significant barriers to their actual realization. We explore the design choices of sharing, or of partitioning and distributing, the front end (instruction cache, instruction fetch, and dispatch), the execution units and associated state, as well as the L1 Dcache banks, in a clustered multi-threaded (CMT) processor. We show that the best performance is obtained by restricting the sharing of the L1 Dcache banks and the execution engines among threads. On the other hand, significant sharing of the front-end resources is the best approach. When compared against large monolithic SMT processors, a CMT processor provides very competitive IPC performance on average, 90-96% of that of partitioned SMT while being more scalable and much more power efficient. In a CMP organization, the gap between SMT and CMT processors shrinks further, making a CMP of CMT processors a highly viable alternative for the future

The memory wall problem is one of the important issues in modern computer system, and it affects the system performance in spite of the powerful processor. The emergence of multi-core processors has further exacerbated the problem???On the other hand, the increasing use of the linked data structure in applications aggravates the memory access latency. This paper utilizes multi-threading technology based on CMP, and dispatches a helper thread when the program is running which prefetches the demanded data into the shared cache in advance to hide the long memory access latency. The helper thread shows great performance by controlling the distance between helper thread and main thread. Simple analysis of the effect of the computation workload between the accesses of the pointers to prefetching is also provided.

Simultaneous multithreading (SMT) and chip-multiprocessor (CMP) are currently two important trends in the design of processors. As the processor executes more than two programs simultaneously, these programs will compete keenly for the use of the cache. This makes it more difficult to predict the worst case computation time (WCET), and might even lead to an overall low efficiency in certain circumstances. Even though the traditional cache partitioning method can solve the foregoing two problems, it reduces the utility rate of the cache as well as the performance of the processor. The method presented in this paper allows the processors to share the cache without affecting each other. It makes the WCET analysis more easily on a multithreaded CPU architecture (e.g., SMT and CMP). Furthermore, the idea of the cache design is based on a power-efficient (i.e., environment friendly) design called ``drowsy cache'' and the power-efficiency feature is inherited.

The limitation imposed by instruction-level parallelism (ILP) has motivated the use of thread-level parallelism (TLP) as a common strategy for improving processor performance. TLP paradigms such as simultaneous multithreading (SMT), chip multiprocessing (CMP) and combinations of both offer the opportunity to obtain higher throughputs. However, they also have to face the challenge of sharing resources of the architecture. Simply avoiding any resource control can lead to undesired situations where one thread is monopolizing all the resources and harming the other threads. Some studies deal with the resource sharing problem in SMTs at core level resources like issue queues, registers, etc. In CMPs, resource sharing is lower than in SMT, focusing in the cache hierarchy.

Speculative multithreading is a technique that has been used to improve single thread performance. Speculative multithreading architectures for Chip multiprocessors (CMPs) have been extensively studied. But there have been relatively few studies on the design of speculative multithreading for simultaneous multithreading (SMT) processors. The current SMT based designs – IMT [9] and DMT [2] use load/store queue (LSQ) to perform dependence checking. Since the size of the LSQ is limited, this design is suitable only for small threads. In this paper we present a novel cache-based architecture support for speculative simultaneous multithreading which can efficiently handle larger threads. In our architecture, the associativity in the cache is used to buffer speculative values. Our 4-thread architecture can achieve about 15% speedup when compared to the equivalent superscalar processors and about 3% speedup on the average over the LSQ-based architectures, however, with a less complex hardware. Also our scheme can perform 14% better than the LSQ-based scheme for larger threads.

The limitation imposed by instruction-level parallelism (ILP) has motivated the use of thread-level parallelism (TLP) as a common strategy for improving processor performance. TLP paradigms such as simultaneous multithreading (SMT), chip multiprocessing (CMP) and combinations of both offer the opportunity to obtain higher throughputs. However, they also have to face the challenge of sharing resources of the architecture. Simply avoiding any resource control can lead to undesired situations where one thread is monopolizing all the resources and harming the other threads. Some studies deal with the resource sharing problem in SMTs at core level resources like issue queues, registers, etc. In CMPs, resource sharing is lower than in SMT, focusing in the cache hierarchy.

The instruction-level parallelism found in a conventional instruction stream is limited. Studies have shown the limits of processor utilization even for today's superscalar microprocessors. One solution is the additional utilization of more coarse-grained parallelism. The main approaches are the (single) chip multiprocessor and the multithreaded processor which optimize the throughput of multiprogramming workloads rather than single-thread performance. The chip multiprocessor integrates two or more complete processors on a single chip. Every unit of a processor is duplicated and used independently of its copies on the chip. In contrast, the multithreaded processor is able to pursue two or more threads of control in parallel within the processor pipeline. Unused instruction slots, which arise from pipelined execution of single-threaded programs by a contemporary microprocessor, are filled by instructions of other threads within a multithreaded processor. The execution units are multiplexed between the threads in the register sets. Underutilization of a superscalar processor due to missing instruction-level parallelism can be overcome by simultaneous multithreading, where a processor can issue multiple instructions from multiple threads each cycle. Simultaneous multithreaded processors combine the multithreading technique with a wide-issue superscalar processor such that the full issue bandwidth is utilized by potentially issuing instructions from different threads simultaneously. This survey paper explains and classifies the various multithreading techniques in research and in commercial microprocessors and compares multithreaded processors with chip multiprocessors.

Simultaneous multithreading is a technique that permits multiple independent threads to issue multiple instructions each cycle. In previous work we demonstrated the performance potential of simultaneous multithreading, based on a somewhat idealized model. In this paper we show that the throughput gains from simultaneous multithreading can be achieved without extensive changes to a conventional wide-issue superscalar, either in hardware structures or sizes. We present an architecture for simultaneous multithreading that achieves three goals: (1) it minimizes the architectural impact on the conventional superscalar design, (2) it has minimal performance impact on a single thread executing alone, and (3) it achieves significant throughput gains when running multiple threads. Our simultaneous multithreading architecture achieves a throughput of 5.4 instructions per cycle, a 2.5-fold improvement over an unmodified superscalar with similar hardware resources. This speedup is enhanced by an advantage of multithreading previously unexploited in other architectures: the ability to favor for fetch and issue those threads most efficiently using the processor each cycle, thereby providing the "best" instructions to the processor.

Networking is considered a datacenter tax, and hyperscalers push hard to provide high-performance networking with minimal resource expenditure. To keep up with the ever-increasing network rates, many CPU cycles are spent on the networking tax. We make a key observation that network processing threads can be simultaneously executed on server CPUs with minimal interference with the application threads. However, utilizing simultaneous multithreading (SMT) to scale the number of network threads with the number of application threads suffers from (1) failing to provide strict tail latency requirements for latency-critical applications, and (2) reducing the number of available hardware threads for application processes, thus contributing to a high datacenter network tax. In this work, we design, implement, and evaluate a chip-multiprocessor (CMP) with specialized Simultaneous Data-delivery Threads (SDT) per physical core. The key insight is that with judicious partitioning at the architectural level, SDT can safely co-run with application processes with guaranteed performance isolation. Our evaluation results, using full-system simulation, show that a 20-core CMP enhanced with SDT reduces the area and power consumption of a baseline 40-core CMP by 47.5% and 66%, respectively, while reducing network throughput by less than 10%.

In Simultaneous Multithreaded (SMT) architectures most hardware resources are shared between threads. This provides a good cost/performance trade-off which renders these architectures suitable for use in embedded systems. However, since threads share many resources, they also interfere with each other. As a result, execution times of applications become highly unpredictable and dependent on the context in which an application is executed. Obviously, this poses problems if an SMT is to be used in a real-time system.In this paper, we propose two novel hardware mechanisms that can be used to reduce this performance variability. In contrast to previous approaches, our proposed mechanisms do not need any information beyond the information already known by traditional job schedulers. Nor do they require extensive profiling of workloads to determine optimal schedules. Our mechanisms are based on dynamic resource partitioning. The OS level job scheduler needs to be slightly adapted in order to provide the hardware resource allocator some information on how this resource partitioning needs to be done. We show that our mechanisms provide high stability for SMT architectures to be used in real-time systems: the real time benchmarks we used meet their deadlines in more than 98% of the cases considered while the other thread in the workload still achieves high throughput.

This paper presents the study of running several core multimedia applications on a simultaneous multithreading (SMT) architecture and derives design principles for multimedia software engineering. The multimedia workloads range from memory to computational-bounded kernels. A performance metric to evaluate effective SMT performance gain is introduced, and compared to similar metrics on symmetric multiprocessor (SMP) systems. In addition, we analyze and compare SMT versus SMP systems, and highlight the advantages in the studied applications. The results indicate that sharing the cache in SMT processors can provide better cache locality and thus better performance although sharing the cache can introduce cache conflicts and reduce the actual cache size available for each logical processor. We also propose mutually beneficial prefetching - a technique to schedule threads so that they prefetch data for each other in order to reduce cache miss penalty.