Rsim: simulating shared-memory multiprocessors with ILP processors

While in the last decade image and video processing (IVP) have gradually moved from special purpose computer architectures based on massive parallelism (MP) to general purpose computer architectures based on instruction-level parallelism (ILP), a new challenge is now to be faced by the IVP community, namely the application of IVP also in small-size embedded systems (e.g., video players, smart cameras, digital diaries, etc.) based on ILP processors. Because of the requirements of low size, weight, and power consumption, these embedded systems do not take advantage of processors that feature advanced dynamic code optimization mechanisms such as those based on instruction reordering and register renaming. On the other hand, the compile time techniques of present generation compilers do not appear to be aggressive enough to exploit the massive parallelism of IVP tasks in ILP architectures, thus leading to inefficient programs. This paper analyzes the efficiency of IVP programs on ILP CPUs. In particular it presents: (1) a reference model for the efficient design and implementation of highly parallel programs, such as the ones of the IVP domain; (2) an analysis of the inefficiencies of IVP programs implemented on ILP processors; and (3) a set of techniques, deriving from the reference model, that overcome these inefficiencies. These techniques are based on a novel computing paradigm called bucket processing.

Current microprocessors aggressively exploit instruction-level parallelism (ILP) through techniques such as multiple issue, dynamic scheduling, and non-blocking reads. Recent work has shown that memory latency remains a significant performance bottleneck for shared-memory multiprocessor systems built of such processors.This paper provides the first study of the effectiveness of software-controlled non-binding prefetching in shared memory multiprocessors built of state-of-the-art ILP-based processors. We find that software prefetching results in significant reductions in execution time (12% to 31%) for three out of five applications on an ILP system. However, compared to previous-generation system, software prefetching is significantly less effective in reducing the memory stall component of execution time on an ILP system. Consequently, even after adding software prefetching, memory stall time accounts for over 30% of the total execution time in four out of five applications on our ILP system.This paper also investigates the interaction of software prefetching with memory consistency models on ILP-based multiprocessors. In particular, we seek to determine whether software prefetching can equalize the performance of sequential consistency (SC) and release consistency (RC). We find that even with software prefetching, for three out of five applications, RC provides a significant reduction in execution time (15% to 40%) compared to SC.

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.

Summary form only given. Speculative executions help modern processors to expose independent instructions on the fly and accordingly exploit more instruction-level parallelism. However, when incorrect speculations occur, useless work is performed for those incorrectly speculated instructions. This lowers a sustained performance and leads to a significant waste of power. Unlike superscalar processors, simultaneous multithreading (SMT) processors can concurrently execute multiple threads. Thus, they have a chance to control speculative executions by deliberately choosing threads from which instructions will be fetched at each cycle, considering the dynamic characteristics of running threads. We present an efficient front-end mechanism, called SAFE-T (speculation-aware front-end throttling), for scheduling threads in SMT processors. It involves thread prioritizing and throttling; priority given to a thread can be overridden when that thread seems to suffer from an excessive amount of incorrect speculations, therefore preventing instructions from being fetched. Simulation results show that our policy provides an average reduction of 41.6% in the number of wrong-path instructions and improves the instruction throughput by up to 14.5%. A cost-effective implementation for the proposed policy is shown as well.

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.

Relaxed consistency models have been shown to significantly outperform sequential consistency for single-issue, statically scheduled processors with blocking reads. However, current microprocessors aggressively exploit instruction-level parallelism (ILP) using methods such as multiple issue, dynamic scheduling, and non-blocking reads. Researchers have conjectured that two techniques, hardware-controlled non-binding prefetching and speculative loads, have the potential to equalize the hardware performance of memory consistency models on such processors.This paper performs the first detailed quantitative comparison of several implementations of sequential consistency and release consistency optimized for aggressive ILP processors. Our results indicate that hardware prefetching and speculative loads dramatically improve the performance of sequential consistency. However, the gap between sequential consistency and release consistency depends on the cache write policy and the complexity of the cache-coherence protocol implementation. In most cases, release consistency significantly outperforms sequential consistency, but for two applications, the use of a write-back primary cache and a more complex cache-coherence protocol nearly equalizes the performance of the two models.We also observe that the existing techniques, which require on-chip hardware modifications, enhance the performance of release consistency only to a small extent. We propose two new software techniques --- fuzzy acquires and selective acquires --- to achieve more overlap than allowed by the previous implementations of release consistency. To enhance methods for overlapping acquires, we also propose a technique to eliminate control dependences caused by an acquire loop, using a small amount of off-chip hardware called the synchronization buffer.

In this paper, we propose a new next generation high-performance micro-architecture based on the combination of simultaneous multithreading and trace processor. By exploiting both Instruction-Level Parallelism and Thread-Level Parallelism, Simultaneous Multithreading Trace Processor can be expected to achieve higher performance than SMT or Trace Processor individual. We describe the organization of SMT Trace Processor architecture and some fundamental techniques. A path-based multiple traces prediction mechanism is also described in the paper.KeywordsProcessing ElementRegister FileData CacheMultiple ThreadInstruction CacheThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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.

Nearly all personal computer and workstation processors, and virtually all high-performance embedded processor cores, now embody instruction level parallel (ILP) processing in the form of superscalar or very long instruction word (VLIW) architectures. ILP processors put much more of a burden on compilers; without heroic compiling techniques, most such processors fall far short of their performance goals. Those techniques are largely found in the high-level optimization phase and in the code generation phase; they are also collectively called instruction scheduling. This paper reviews the state of the art in code generation for ILP parallel processors. Modern ILP code generation methods move code across basic block boundaries. These methods grew out of techniques for generating horizontal microcode, so we introduce the problem by describing its history. Most modem approaches can be categorized by the shape of the scheduling region. Some of these regions are loops, and for those techniques known broadly as are used. Software Pipelining techniques are only considered here when there are issues relevant to the region-based techniques presented. The selection of a type of region to use in this process is one of the most controversial questions in code generation; the paper surveys the best known alternatives. The paper then considers two questions: First, given a type of region, how does one pick specific regions of that type in the intermediate code. In conjunction with region selection, we consider region enlargement techniques such as unrolling and branch target expansion. The second question, how does one construct a schedule once regions have been selected, occupies the next section of the paper. Finally, schedule construction using recent, innovative resource modeling based on finite-state automata is then reexamined. The paper includes an extensive bibliography.

By converting thread-level parallelism to instruction level parallelism, simultaneous multithreaded (SMT) processors are emerging as effective ways to utilize the resources of modern superscalar architectures. However, the full potential of SMT has not yet been reached as most modern operating systems use existing single-thread or multiprocessor algorithms to schedule threads, neglecting contention for resources between threads. To date, even the best SMT scheduling algorithms simply try to group threads for co-residency based on each thread's expected resource utilization but do not take into account variance in thread behavior. As such, we introduce architectural support that enables new thread scheduling algorithms to group threads for co-residency based on fine-grain memory system activity information. The proposed memory monitoring framework centers on the concept of a cache activity vector, which exposes runtime cache resource information to the operating system to improve job scheduling. Using this scheduling technique, we experimentally evaluate the overall performance improvement of workloads on an SMT machine compared against the most recent Linux job scheduler. This work is first motivated with experiments in a simulated environment, then validated on a hyperthreading-enabled Intel Pentium-4 Xeon microprocessor running a modified version of the latest Linux kernel.

As wireless video products evolve, they demand more sophisticated processing at higher resolutions and frame rates. Computational performance and energy efficiency have become critical design issues. This paper presents the Quantized Color Pack eXtension (QCPX) combined with a loop unrolling (LU) technique to improve execution performance and energy efficiency of color image and video processing applications. QCPX applied to a 32-bit datapath processor supports parallel operations on two packed 16-bit YCbCr (Y: luminance, Cr and Cb: chrominance) color pixels, providing greater subword-level parallelism by increasing the number of smaller color pixels packed into a word. Instruction-level parallelism can be further enhanced through loop unrolling. These techniques provide greater performance and efficiency for multimedia workloads on mobile systems. Experimental results on a set of media benchmark applications indicate that the LU plus QCPX-optimized version achieves a speedup ranging from 3.8 to 7.9 while reducing the energy consumption from 76% to 87% over the baseline version on identically configured, dynamically scheduled ILP superscalar processors. The LU plus QCPX-optimized version also outperforms the LU plus MDMX-like (MIPS’s multimedia extension) version.

Multimedia instruction set extensions has become a prominent feature in desktop microprocessor platforms, promising superior performance on a wide range of floating-point and integer signal processing, multimedia, and scientific applications. Nevertheless, the question remains whether or not these multimedia extensions can be applied to improve the performance of general, integer intensive applications. The answer to this question is important and could be used to direct research and development of compiler algorithms and refinements to multimedia architectures. In this paper, we answer the question of whether integer programs exhibit enough sub-word level parallelism (SLP) to facilitate performance improvements through use of multimedia extensions. Using a highly optimizing compiler and a simulator for an aggressive SLP architecture, we measured available SLP in a range of integer benchmarks. Our measurements show that these applications exhibit significant levels of SLP. Using the most aggressive simulator settings, dynamic instruction count reductions of 17 to 36 percent were observed. However, detailed examination of the data indicates that much of this parallelism is equivalent to instruction-level parallelism (ILP) and could just as easily be exploited by a traditional ILP architecture. Our findings indicate that researchers should focus their efforts on exploiting SLP in floating-point intensive and multimedia applications.

This paper presents a new parallelization model, called coarse-grained thread pipelining, for exploiting speculative coarse-grained parallelism from general-purpose application programs in shared-memory multiprocessor systems. This parallelization model, which is based on the fine-grained thread pipelining model proposed for the superthreaded architecture, allows concurrent execution of loop iterations in a pipelined fashion with runtime data-dependence checking and control speculation. The speculative execution combined with the runtime dependence checking allows the parallelization of a variety of program constructs that cannot be parallelized with existing runtime parallelization algorithms. The pipelined execution of loop iterations in this new technique results in lower parallelization overhead than in other existing techniques. We evaluated the performance of this new model using some real applications and a synthetic benchmark. These experiments show that programs with a sufficiently large grain size compared to the parallelization overhead obtain significant speedup using this model. The results from the synthetic benchmark provide a means for estimating the performance that can be obtained from application programs that will be parallelized with this model. The library routines developed for this thread pipelining model are also useful for evaluating the correctness of the codes generated by the superthreaded compiler and in debugging and verifying the simulator for the superthreaded processor.

Shared-memory multiprocessor systems can achieve high performance levels when appropriate work parallelization and data distribution are performed. These two actions are not independent and decisions have to be taken in a unified way trying to minimize execution time and data movement costs. The first goal is achieved by parallelizing loops (the main components suitable for parallel execution in scientific codes) and assign work to processors having in mind a good load balancing. The second goal is achieved when data is stored in the cache memories of processors minimizing both true and false sharing of cache lines. This paper describes the main features of our automatic parallelization and data distribution research tool and shows the performance of the parallelization strategies generated. The tool (named PDDT) accepts programs written in Fortran77 and generates directives of shared memory programming models (like Power Fortran from SGI or Exemplar from Convex).KeywordsHigh Performance CompilersLoop ParallelizationStatic and Dynamic Data MappingsCache BehaviorShared Memory Multiprocessors

In modern microprocessors, the access time of register file becomes a critical part in total delay. Instruction level or thread level parallelism improves instructions per cycle (IPC) by executing multiple instructions in one cycle. Such multiple instructions need to read or write data from/to register files simultaneously. To satisfy that, register file with sufficient ports should be designed. However, the area and access time of register file with large ports will increase sharply. Duplicated register file (DupRF) architecture can reduce access time by distributing read ports. In this paper, we propose a new kind of DupRF architecture for embedded simultaneous multithreading (SMT) microprocessor and estimate the effect with respect to the area and access time. Especially, we measure the product of area and access time as computation cost. For a SMT microprocessor with 6 threads, 64-bit data-width and 6 function units, 3-duplicate register file architecture can reduce access time by 12.61% with a slight increase of computation cost by 3.35% compared with the central register file architecture