Architectural support for task dependence management with flexible software scheduling

The growing complexity of multi-core architectures has motivated a wide range of software mechanisms to improve the orchestration of parallel executions. Task parallelism has become a very attractive approach thanks to its programmability, portability and potential for optimizations. However, with the expected increase in core counts, finer-grained tasking will be required to exploit the available parallelism, which will increase the overheads introduced by the runtime system. This work presents Task Dependence Manager (TDM), a hardware/software co-designed mechanism to mitigate runtime system overheads. TDM introduces a hardware unit, denoted Dependence Management Unit (DMU), and minimal ISA extensions that allow the runtime system to offload costly dependence tracking operations to the DMU and to still perform task scheduling in software. With lower hardware cost, TDM outperforms hardware-based solutions and enhances the flexibility, adaptability and composability of the system. Results show that TDM improves performance by 12.3% and reduces EDP by 20.4% on average with respect to a software runtime system. Compared to a runtime system fully implemented in hardware, TDM achieves an average speedup of 4.2% with 7.3x less area requirements and significant EDP reductions. In addition, five different software schedulers are evaluated with TDM, illustrating its flexibility and performance gains.This work has been supported by the RoMoL ERC Advanced Grant (GA 321253), by the European HiPEAC Network of Excellence, by the Spanish Ministry of Science and Innovation (contracts TIN2015-65316-P, TIN2016-76635-C2-2-R and TIN2016-81840-REDT), by the Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272), and by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 671697 and No. 671610. M. Moretó has been partially supported by the Ministry of Economy and Competitiveness under Juan de la Cierva postdoctoral fellowship number JCI-2012-15047.Peer ReviewedPostprint (author's final draft

RingScalar: A Complexity-Effective Out-of-Order Superscalar Microarchitecture

RingScalar is a complexity-effective microarchitecture for out-of-order superscalar processors, that reduces the area, latency, and power of all major structures in the instruction flow. The design divides an N-way superscalar into N columns connected in a unidirectional ring, where each column contains a portion of the instruction window, a bank of the register file, and an ALU. The design exploits the fact that most decoded instructions are waiting on just one operand to use only a single tag per issue window entry, and to restrict instruction wakeup and value bypass to only communicate with the neighboring column. Detailed simulations of four-issue single-threaded machines running SPECint2000 show that RingScalar has IPC only 13% lower than an idealized superscalar, while providing large reductions in area, power, and circuit latency

Exploiting Fine-Grain Concurrency Analytical Insights in Superscalar Processor Design

This dissertation develops analytical models to provide insight into various design issues associated with superscalar-type processors, i.e., the processors capable of executing multiple instructions per cycle. A survey of the existing machines and literature has been completed with a proposed classification of various approaches for exploiting fine-grain concurrency. Optimization of a single pipeline is discussed based on an analytical model. The model-predicted performance curves are found to be in close proximity to published results using simulation techniques. A model is also developed for comparing different branch strategies for single-pipeline processors in terms of their effectiveness in reducing branch delay. The additional instruction fetch traffic generated by certain branch strategies is also studied and is shown to be a useful criterion for choosing between equally well performing strategies. Next, processors with multiple pipelines are modelled to study the tradeoffs associated with deeper pipelines versus multiple pipelines. The model developed can reveal the cause of performance bottleneck: insufficient resources to exploit discovered parallelism, insufficient instruction stream parallelism, or insufficient scope of concurrency detection. The cost associated with speculative (i.e., beyond basic block) execution is examined via probability distributions that characterize the inherent parallelism in the instruction stream. The throughput prediction of the analytic model is shown, using a variety of benchmarks, to be close to the measured static throughput of the compiler output, under resource and scope constraints. Further experiments provide misprediction delay estimates for these benchmarks under scope constraints, assuming beyond-basic-block, out-of-order execution and run-time scheduling. These results were derived using traces generated by the Multiflow TRACE SCHEDULING™(*) compacting C and FORTRAN 77 compilers. A simplified extension to the model to include multiprocessors is also proposed. The extended model is used to analyze combined systems, such as superpipelined multiprocessors and superscalar multiprocessors, both with shared memory. It is shown that the number of pipelines (or processors) at which the maximum throughput is obtained is increasingly sensitive to the ratio of memory access time to network access delay, as memory access time increases. Further, as a function of inter-iteration dependency distance, optimum throughput is shown to vary nonlinearly, whereas the corresponding Optimum number of processors varies linearly. The predictions from the analytical model agree with published results based on simulations. (*)TRACE SCHEDULING is a trademark of Multiflow Computer, Inc

Late allocation and early release of physical registers

The register file is one of the critical components of current processors in terms of access time and power consumption. Among other things, the potential to exploit instruction-level parallelism is closely related to the size and number of ports of the register file. In conventional register renaming schemes, both register allocation and releasing are conservatively done, the former at the rename stage, before registers are loaded with values, and the latter at the commit stage of the instruction redefining the same register, once registers are not used any more. We introduce VP-LAER, a renaming scheme that allocates registers later and releases them earlier than conventional schemes. Specifically, physical registers are allocated at the end of the execution stage and released as soon as the processor realizes that there will be no further use of them. VP-LAER enhances register utilization, that is, the fraction of allocated registers having a value to be read in the future. Detailed cycle-level simulations show either a significant speedup for a given register file size or a reduction in the register file size for a given performance level, especially for floating-point codes, where the register file pressure is usually high.Peer ReviewedPostprint (published version

Beyond Dataflow

This paper presents some recent advanced dataflow architectures. While the dataflow concept offers the potential of high performance, the performance of an actual dataflow implementation can be restricted by a limited number of functional units, limited memory bandwidth, and the need to associatively match pending operations with available functional units. Since the early 1970s, there have been significant developments in both fundamental research and practical realizations of dataflow models of computation. In particular, there has been active research and development in multithreaded architectures that evolved from the dataflow model. Also some other techniques for combining control-flow and dataflow emerged, such as coarse-grain dataflow, dataflow with complex machine operations, RISC dataflow, and micro dataflow. These developments have also had certain impact on the conception of highperformance superscalar processors in the “post-RISC” era

Application of compiler-assisted multiple instruction rollback recovery to speculative execution

Speculative execution is a method to increase instruction level parallelism which can be exploited by both super-scalar and VLIW architectures. The key to a successful general speculation strategy is a repair mechanism to handle mispredicted branches and accurate reporting of exceptions for speculated instructions. Multiple instruction rollback is a technique developed for recovery from transient processor failure. Many of the difficulties encountered during recovery from branch misprediction or from instruction re-execution due to exception in a speculative execution architecture are similar to those encountered during multiple instruction rollback. The applicability of a recently developed compiler-assisted multiple instruction rollback scheme to aid in speculative execution repair is investigated. Extensions to the compiler-assisted scheme to support branch and exception repair are presented along with performance measurements across ten application programs

Instruction fetch architectures and code layout optimizations

The design of higher performance processors has been following two major trends: increasing the pipeline depth to allow faster clock rates, and widening the pipeline to allow parallel execution of more instructions. Designing a higher performance processor implies balancing all the pipeline stages to ensure that overall performance is not dominated by any of them. This means that a faster execution engine also requires a faster fetch engine, to ensure that it is possible to read and decode enough instructions to keep the pipeline full and the functional units busy. This paper explores the challenges faced by the instruction fetch stage for a variety of processor designs, from early pipelined processors, to the more aggressive wide issue superscalars. We describe the different fetch engines proposed in the literature, the performance issues involved, and some of the proposed improvements. We also show how compiler techniques that optimize the layout of the code in memory can be used to improve the fetch performance of the different engines described Overall, we show how instruction fetch has evolved from fetching one instruction every few cycles, to fetching one instruction per cycle, to fetching a full basic block per cycle, to several basic blocks per cycle: the evolution of the mechanism surrounding the instruction cache, and the different compiler optimizations used to better employ these mechanisms.Peer ReviewedPostprint (published version