Fred: an architecture for a self-timed decoupled computer

Journal ArticleDecoupled computer architectures provide an effective means of exploiting instruction level parallelism. Selftimed micropipeline systems are inherently decoupled due to the elastic nature of the basic FIFO structure, and may be ideally suited for constructing decoupled computer architectures. Fred is a self-timed decoupled, pipelined computer architecture based on micropipelines. We present the architecture of Fred, with specific details on a micropipelined implementation that includes support for multiple functional units and out-of-order instruction completion due to the self-timed decoupling

Fred: an architecture for a self-timed decoupled computer

Journal ArticleDecoupled computer architectures provide an effective means of exploiting instruction level parallelism. Self-timed micropipeline systems are inherently decoupled due to the elastic nature of the basic FIFO structure, and may be ideally suited for constructing decoupled computer architectures. Fred is a self-timed decoupled, pipelined computer architecture based on micropipelines. We present the architecture of Fred, with specific details on a micropipelined implementation that includes support for multiple functional units and out-of- order instruction completion due to the self-timed decoupling

Precise exception handling for a self-timed processor

Journal ArticleSelf-timed systems structured as multiple concurrent processes and communicating through self-timed queues are a convenient way to implement decoupled computer architectures. Machines of this type can exploit instruction level parallelism in a natural way, and can be easily modified and extended. However, providing a precise exception model for a self-timed micropipelined processor can be difficult, since the processor state does not change at uniformly discrete intervals. We present a precise exception method implemented for Fred, a self-timed, decoupled, pipelined computer architecture with out-of-order instruction completion

Dynamically managing the communication-parallelism trade-off in future clustered processors

Journal ArticleClustered microarchitectures are an attractive alternative to large monolithic superscalar designs due to their potential for higher clock rates in the face of increasingly wire-delay-constrained process technologies. As increasing transistor counts allow an increase in the number of clusters, thereby allowing more aggressive use of instruction-level parallelism (ILP), the inter-cluster communication increases as data values get spread across a wider area. As a result of the emergence of this trade-off between communication and parallelism, a subset of the total on-chip clusters is optimal for performance. To match the hardware to the application's needs, we use a robust algorithm to dynamically tune the clustered architecture. The algorithm, which is based on program metrics gathered at periodic intervals, achieves an 11% performance improvement on average over the best statically defined architecture. We also show that the use of additional hardware and reconfiguration at basic block boundaries can achieve average improvements of 15%. Our results demonstrate that reconfiguration provides an effective solution to the communication and parallelism trade-off inherent in the communication-bound processors of the future

Dynamically allocating processor resources between nearby and distant ILP

Journal ArticleModern superscalar processors use wide instruction issue widths and out-of-order execution in order to increase instruction-level parallelism (ILP). Because instructions must be committed in order so as to guarantee precise exceptions, increasing ILP implies increasing the sizes of structures such as the register file, issue queue, and reorder buffer. Simultaneously, cycle time constraints limit the sizes of these structures, resulting in conflicting design requirements. In this paper, we present a novel microarchitecture designed to overcome the limitations of a register file size dictated by cycle time constraints. Available registers are dynamically allocated between the primary program thread and a future thread. The future thread executes instructions when the primary thread is limited by resource availability. The future thread is not constrained by in-order commit requirements. It is therefore able to examine a much larger instruction window and jump far ahead to execute ready instructions. Results are communicated back to the primary thread by warming up the register file, instruction cache, data cache, and instruction reuse buffer, and by resolving branch mispredicts early. The proposed microarchitecture is able to get an overall speedup of 1.17 over the base processor for our benchmark set, with speedups of up to 1.64

High Throughput Virtual Screening with Data Level Parallelism in Multi-core Processors

Improving the throughput of molecular docking, a computationally intensive phase of the virtual screening process, is a highly sought area of research since it has a significant weight in the drug designing process. With such improvements, the world might find cures for incurable diseases like HIV disease and Cancer sooner. Our approach presented in this paper is to utilize a multi-core environment to introduce Data Level Parallelism (DLP) to the Autodock Vina software, which is a widely used for molecular docking software. Autodock Vina already exploits Instruction Level Parallelism (ILP) in multi-core environments and therefore optimized for such environments. However, with the results we have obtained, it can be clearly seen that our approach has enhanced the throughput of the already optimized software by more than six times. This will dramatically reduce the time consumed for the lead identification phase in drug designing along with the shift in the processor technology from multi-core to many-core of the current era. Therefore, we believe that the contribution of this project will effectively make it possible to expand the number of small molecules docked against a drug target and improving the chances to design drugs for incurable diseases.Comment: Information and Automation for Sustainability (ICIAfS), 2012 IEEE 6th International Conference o

Memory and Parallelism Analysis Using a Platform-Independent Approach

Emerging computing architectures such as near-memory computing (NMC) promise improved performance for applications by reducing the data movement between CPU and memory. However, detecting such applications is not a trivial task. In this ongoing work, we extend the state-of-the-art platform-independent software analysis tool with NMC related metrics such as memory entropy, spatial locality, data-level, and basic-block-level parallelism. These metrics help to identify the applications more suitable for NMC architectures.Comment: 22nd ACM International Workshop on Software and Compilers for Embedded Systems (SCOPES '19), May 201

Quantifying the benefits of SPECint distant parallelism in simultaneous multithreading architectures

We exploit the existence of distant parallelism that future compilers could detect and characterise its performance under simultaneous multithreading architectures. By distant parallelism we mean parallelism that cannot be captured by the processor instruction window and that can produce threads suitable for parallel execution in a multithreaded processor. We show that distant parallelism can make feasible wider issue processors by providing more instructions from the distant threads, thus better exploiting the resources from the processor in the case of speeding up single integer applications. We also investigate the necessity of out-of-order processors in the presence of multiple threads of the same program. It is important to notice at this point that the benefits described are totally orthogonal to any other architectural techniques targeting a single thread.Peer ReviewedPostprint (published version