High-performance Superscalar Processors Research Articles

Transformations for High-Performance Computing

In the last three decades a large number of compiler transformations for optimizing programs have been implemented. Most optimizations for uniprocessors reduce the number of instructions executed by the program using transformations based on the analysis of scalar quantities and data-flow techniques. In contrast, optimizations for high-performance superscalar, vector, and parallel processors maximize parallelism and memory locality with transformations that rely on tracking the properties of arrays using loop dependence analysis. This survey is a comprehensive overview of the important high-level program restructuring techniques for imperative languages such as C and Fortran. Transformations for both sequential and various types of parallel architectures are covered in depth. We describe the purpose of each transformation, explain how to determine if it is legal, and give an example of its application.

Energy Efficient Dual Issue Embedded Processor

While energy efficiency is essential to extend the battery life of embedded devices, performance cannot be ignored. High performance superscalar embedded processors are more energy efficient than low performance scalar processors, however, they consume more power which is very limited in battery o

Researches on Design and Implementations of Two 2-Bit Predictors

High-performance superscalar processors, which can be used in building base-stations of cell phones and cloud-based web servers, rely heavily on aggressive branch predictors to avoid stalls no matter the branch is taken or not. Dynamic branch predictor which is based on the historical records of the previously executed branches always outputs good performance. Two-bit predictor discussed in this paper is one of the most popular ones that always practically employed. This paper demonstrates two implementations of two-bit predictors. Using BTB to process solo conditional branches is the first one, which is normally used. Other categories of branch instructions may results in several bubbles as the penalty. While the other implementation employs BTB dealing with all kinds of branch instructions, generating target addresses without any delay cycle. Simulation results show that the second implementation has much better performance than the former one. It decreases the mis-prediction rate from 12.26% to 11.48%, and also has much higher prediction accuracy on indirect jumps. With these results, we have our predictor re-designed accordingly and implemented successfully in superscalar processors.

Performance Evaluation of Dynamic Speculative Multithreading with the Cascadia Architecture

Thread-level parallelism (TLP) has been extensively studied in order to overcome the limitations of exploiting instruction-level parallelism (ILP) on high-performance superscalar processors. One promising method of exploiting TLP is dynamic speculative multithreading (D-SpMT), which extracts multiple threads from a sequential program without compiler support or instruction set extensions. This paper introduces Cascadia, a D-SpMT multicore architecture that provides multigrain thread-level support and is used to evaluate the performance of several benchmarks. Cascadia applies a unique sustainable IPC (sIPC) metric on a comprehensive loop tree to select the best performing nested loop level to multithread. This paper also discusses the relationships that loops have on one another, in particular, how loop nesting levels can be extended through procedures. In addition, a detailed study is provided on the effects that thread granularity and interthread dependencies have on the entire system.

Investigating the effects of fine-grain three-dimensional integration on microarchitecture design

In this article we propose techniques that enable efficient exploration of the 3D design space, where each logical block can span more than one silicon layer. Fine-grain 3D integration provides reduced intrablock wire delay as well as improved power consumption. However, the corresponding power and performance advantage is usually underutilized, since various implementations of multilayer blocks require novel physical design and microarchitecture infrastructure to explore 3D microarchitecture design space. We develop a cubic packing engine which can simultaneously optimize physical and architectural design for efficient vertical integration. This technique selects the individual unit designs from a set of single-layer or multilayer implementations to get the best microarchitectural design in terms of performance, temperature, or both. Our experimental results using a design driver of a high-performance superscalar processor show a 36% performance improvement over traditional 2D for 2--4 layers and 14% over 3D with single-layer unit implementations. Since thermal characteristics of 3D integrated circuits are among the main challenges, thermal-aware floorplanning and thermal via insertion techniques are employed to keep the peak temperatures below threshold.

Scalable Dynamic Instruction Scheduler through Wake-Up Spatial Locality

In a high-performance superscalar processor, the instruction scheduler often comes with poor scalability and high complexity due to the expensive wake-up operation. From detailed simulation-based analyses, we find that 95 percent of the wake-up distances between two dependent instructions are short, in the range of 16 instructions, and 99 percent are in the range of 31 instructions. We apply this wake-up spatial locality to the design of conventional CAM-based and matrix-based wakeup logic, respectively. By limiting the wake-up coverage to i + 16 instructions, where 0 les i les 15 for 16-entry segments, the proposed wake-up designs confine the wake-up operation to two matrix-based or three CAM-based 16-entry segments no matter how large the issue window size is. The experimental results show that, for an issue window of 128 entries (IW128) or 256 entries (IW256), the proposed CAM-based wake-up locality design saves 65 percent (IW128) and 76 percent (IW256) of the power consumption and reduces 44 percent (IW128) and 78 percent (IW256) in the wake-up latency compared to the conventional CAM-based design with almost no performance loss. For the matrix-based wake-up logic, applying wake-up locality to the design drastically reduces the area cost. Extensive simulation results, including comparisons with previous works, show that the wake-up spatial locality is the key element to achieving scalability for future sophisticated instruction schedulers.

The Coming Wave of Multithreaded Chip Multiprocessors

The performance of microprocessors has increased exponentially for over 35 years. However, process technology challenges, chip power constraints, and difficulty in extracting instruction-level parallelism are conspiring to limit the performance of future individual processors. To address these limits, the computer industry has embraced chip multiprocessing (CMP), predominately in the form of multiple high-performance superscalar processors on the same die. We explore the trade-off between building CMPs from a few high-performance cores or building CMPs from a large number of lower-performance cores and argue that CMPs built from a larger number of lower-performance cores can provide better performance and performance/Watt on many commercial workloads. We examine two multi-threaded CMPs built using a large number of processor cores: Sun's Niagara and Niagara 2 processors. We also explore the programming issues for CMPs with large number of threads. The programming model for these CMPs is similar to the widely used programming model for symmetric multiprocessors (SMPs), but the greatly reduced costs associated with communication of data through the on-chip shared secondary cache allows for more fine-grain parallelism to be effectively exploited by the CMR Finally, we present performance comparisons between Sun's Niagara and more conventional dual-core processors built from large superscalar processor cores. For several key server workloads, Niagara shows significant performance and even more significant performance/Watt advantages over the CMPs built from traditional superscalar processors.

Power Estimation of Partitioned Register Files in a Clustered Architecture with Performance Evaluation

High power consumption and slow access of enlarged and multiported register files make it difficult to design high performance superscalar processors. The clustered architecture, where the conventional monolithic register file is partitioned into several smaller register files, is expect to overcome the register file issues. In the clustered architecture, the more a monolithic register file is partitioned, the lower power and faster access register files can be realized. However, the partitioning causes losses of IPC (instructions per clock cycle) due to communication among register files. Therefore, degree of partitioning has a strong impact on the trade-off between power consumption and performance. In addition, the organization of partitioned register files also affects the trade-off. In this paper, we attempt to investigate appropriate degrees of partitioning and organizations of partitioned register files in a clustered architecture to assess the trade-off. From the results of execute-driven simulation, we find that the organization of register files and the degree of partitioning have a strong impact on the IPC, and the configuration with non-consistent register files can make use of the partitioned resources more effectively. From the results of register file access time and energy modeling, we find that the configurations with the highly partitioned non-consistent register file organization can receive benefit of the partitioning in terms of operating frequency and access energy of register files. Further, we examine relationship between IPS (instructions per second) and the product of IPC and operating frequency of register files. The results suggest that highly partitioned non-consistent configurations tends to gain more advantage in performance and power.

Performance/Watt

Transaction processing has emerged as the killer application for commercial servers. Most servers are engaged in transactional workloads such as processing search requests, serving middleware, evaluating decisions, managing databases, and powering online commerce. Currently, commercial servers are built from one or more high-performance superscalar processors. However, commercial server applications exhibit high cache miss rates, large memory footprints, and low instruction level parallelism (ILP), which leads to poor utilization on traditional ILP-focused superscalar processors [11]. In addition, these ILP-focused processors have been primarily optimized to deliver maximum performance by employing high clock rates and large amounts of speculation. As a result, we are now at the point where the performance/Watt of subsequent generations of traditional ILP-focused processors on server workloads has been flat [4] or even decreasing. The lack of increase in processor performance/Watt, coupled with the continued decrease in server hardware acquisition costs and likely increases in future power and cooling costs is leading to a situation where total cost of server ownership will soon be predominately determined by power [4]. In this paper, we argue that attacking thread-level parallelism (TLP) via a large number of simple cores on a chip multiprocessor (CMP) leads to much better performance/Watt for server workloads. As a case study, we compare Sun's TLP-oriented Niagara processor against the ILP-oriented dual-core Pentium Extreme Edition from Intel, showing that the Niagara processor has a significant performance/Watt advantage for throughput-oriented server applications.

A low-complexity fetch architecture for high-performance superscalar processors

Fetch engine performance is a key topic in superscalar processors, since it limits the instruction-level parallelism that can be exploited by the execution core. In the search of high performance, the fetch engine has evolved toward more efficient designs, but its complexity has also increased.In this paper, we present the stream fetch engine, a novel architecture based on the execution of long streams of sequential instructions, taking maximum advantage of code layout optimizations. We describe our design in detail, showing that it achieves high fetch performance, while requiring less complexity than other state-of-the-art fetch architectures.

세트 연관 캐쉬를 사용한 2단계 적응적 분기 예측

Conditional branches can severely limit the performance of instruction level parallelism by causing branch penalties. 2-level adaptive branch predictors were developed to get accurate branch prediction in high performance superscalar processors. Although 2 level adaptive branch predictors achieve very high prediction accuracy, they tend to be very costly. In this paper, set-associative cached correlated 2-level branch predictors are proposed to overcome the cost problem in conventional 2-level adaptive branch predictors. According to simulation results, cached correlated predictors deliver higher prediction accuracy than conventional predictors at a significantly lower cost. The best misprediction rates of global and local cached correlated predictors using set-associative caches are 5.99% and 6.28% respectively. They achieve 54% and 17% improvements over those of the conventional 2-level adaptive branch predictors.

Branch prediction using both global and local branch history information

As the pipeline depth and issue rate of high-performance superscalar processors increase, the importance of an excellent branch predictor becomes more crucial to delivering the potential performance of a wide-issue, deep pipelined processor. Conventional two-level branch predictors predict the outcome of a branch either based on the local branch history information, comprising the previous outcomes of a single branch, or based on the global branch history information, comprising the previous outcomes of all branches. The authors propose a new branch prediction scheme, called LGshare, which employs both the global and local branch history information simultaneously to improve the branch prediction accuracy for superscalar processors. It is shown that LGshare can achieve higher branch prediction accuracy than conventional two-level predictors when the size of the pattern history table is fixed.

High-bandwidth x86 instruction fetching based on instruction pointer table

Providing higher degree superscalar instruction fetching is a major concern in a high performance superscalar processor design. In x86 architectures, the variable-length instructions make fetching multiple instructions in a cycle difficult. A common practice is to use predecoded information to help in instruction fetching, while the complex instruction formats induce high redundancies in storing and processing the pre-decoded information in the cache. In the paper, the authors propose to use an Instruction Identifier to predict instruction length and store the instruction pointers as superscalar instruction group indicators. With this method, the difficulty of achieving a high instruction fetch degree (>3) can be overcome. Simulation results suggest that the Instruction Identifier with a 64-entry table is a good performance/cost choice. In the meantime, as the table size decreases, the prediction scheme becomes increasingly important. Moreover, simulation and circuit synthesis show that this design is feasible for high clock rate design.

Energy-effective issue logic

The issue logic of a dynamically-scheduled superscalar processor is a complex mechanism devoted to start the execution of multiple instructions every cycle. Due to its complexity, it is responsible for a significant percentage of the energy consumed by a microprocessor. The energy consumption of the issue logic depends on several architectural parameters, the instruction issue queue size being one of the most important. In this paper we present a technique to reduce the energy consumption of the issue logic of a high-performance superscalar processor. The proposed technique is based on the observation that the conventional issue logic wastes a significant amount of energy for useless activity. In particular, the wake-up of empty entries and operands that are ready represents an important source of energy waste. Besides, we propose a mechanism to dynamically reduce the effective size of the instruction queue. We show that on average the effective instruction queue size can be reduced by a factor of 26% with minimal impact on performance. This reduction together with the energy saved for empty and ready entries result in about 90.7% reduction in the energy consumed by the wake-up logic, which represents 14.9% of the total energy of the assumed processor.

System-level power consumption modeling and tradeoff analysis techniques for superscalar processor design

This paper presents systematic techniques to find low-power high-performance superscalar processors tailored to specific user applications. The model of power is novel because it separates power into architectural and technology components. The architectural component is found via trace-driven simulation, which also produces performance estimates. An example technology model is presented that estimates the technology component, along with critical delay time and real estate usage. This model is based on case studies of actual designs. It is used to solve an important problem: decreasing power consumption in a superscalar processor without greatly impacting performance. Results are presented from runs using simulated annealing to reduce power consumption subject to performance reduction bounds. The major contributions of this paper are the separation of architectural and technology components of dynamic power the use of trace-driven simulation for architectural power measurement, and the use of a near-optimal search to tailor a processor design to a benchmark.

Target prediction for indirect jumps

As the issue rate and pipeline depth of high performance superscalar processors increase, the amount of speculative work issued also increases. Because speculative work must be thrown away in the event of a branch misprediction, wide-issue, deeply pipelined processors must employ accurate branch predictors to effectively exploit their performance potential. Many existing branch prediction schemes are capable of accurately predicting the direction of conditional branches. However, these schemes are ineffective in predicting the targets of indirect jumps achieving, on average, a prediction accuracy rate of 51.8% for the SPECint95 benchmarks. In this paper, we propose a new prediction mechanism, the target cache, for predicting indirect jump targets. For the perl and gcc benchmarks, this mechanism reduces the indirect jump misprediction rate by 93.4% and 63.35% and the overall execution time by 14% and 5%.

A superscalar architecture to exploit instruction level parallelism

If a high-performance superscalar processor is to realise its full potential, the compiler must re-order or schedule the object code at compile time. This scheduling creates groups of adjacent instructions that are independent and which therefore can be issued and executed in parallel at run time. This paper provides an overview of the Hatfield Superscalar Architecture (HSA), a multipleinstruction-issue architecture developed at the University of Hertfordshire to support the development of high-performance instruction schedulers. The long-term objective of the HSA project is to develop the scheduling technology to realise an order of magnitude performance improvement over traditional RISC designs. The paper also presents results from the first HSA instruction scheduler that currently achieves a speedup of over three compared to a classic RISC processor.

Compiler transformations for high-performance computing

In the last three decades a large number of compiler transformations for optimizing programs have been implemented. Most optimizations for uniprocessors reduce the number of instructions executed by the program using transformations based on the analysis of scalar quantities and data-flow techniques. In contrast, optimizations for high-performance superscalar, vector, and parallel processors maximize parallelism and memory locality with transformations that rely on tracking the properties of arrays using loop dependence analysis. This survey is a comprehensive overview of the important high-level program restructuring techniques for imperative languages, such as C and Fortran. Transformations for both sequential and various types of parallel architectures are covered in depth. We describe the purpose of each transformation, explain how to determine if it is legal, and give an example of its application. Programmers wishing to enhance the performance of their code can use this survey to improve their understanding of the optimizations that compilers can perform, or as a reference for techniques to be applied manually. Students can obtain an overview of optimizing compiler technology. Compiler writers can use this survey as a reference for most of the important optimizations developed to date, and as bibliographic reference for the details of each optimization. Readers are expected to be familiar with modern computer architecture and basic program compilation techniques.

POWER2 fixed-point, data cache, and storage control units

The POWER2™ fixed-point, data cache, and storage control units provide a tightly integrated subunit for a second-generation high-performance superscalar RISC processor. These functional units provide dual fixed-point execution units and a large multiported data cache, as well as high-performance interfaces to memory, I/O, and the other execution units in the processor. These units provide the following features: dual fixed-point execution units, improved fixed-point/floating-point synchronization, new floating-point load and store quadword instructions, improved address translation, improved fixed-point multiply/divide, large multiported D-cache, increased bandwidth into and out of the caches through wider data buses, an improved external interrupt mechanism, and an improved I/O DMA mechanism to support multiple-streaming Micro Channels®.

An investigation of the performance of various dynamic scheduling techniques

An important design decision in the implementation of a superscalar processor is the amount of hardware to allocate to the instruction scheduling mechanism. Dynamic scheduling provides, at the cost of (possibly substantial) additional hardware, the potential to improve upon a static schedule by incorporating run-tame information in the scheduling decision. In this study we model several diflerent scheduling techniques and machine configurations. We measure the performance of these models on seven integer and floating point benchmarks taken from the SPEC89 suite. We reporl the results of these measurements and their implications with respect to the design of high performance superscalar processors.