Speculative Segmented Sum for Sparse Matrix-Vector Multiplication on Heterogeneous Processors

Sparse matrix-vector multiplication (SpMV) is a central building block for scientific software and graph applications. Recently, heterogeneous processors composed of different types of cores attracted much attention because of their flexible core configuration and high energy efficiency. In this paper, we propose a compressed sparse row (CSR) format based SpMV algorithm utilizing both types of cores in a CPU-GPU heterogeneous processor. We first speculatively execute segmented sum operations on the GPU part of a heterogeneous processor and generate a possibly incorrect results. Then the CPU part of the same chip is triggered to re-arrange the predicted partial sums for a correct resulting vector. On three heterogeneous processors from Intel, AMD and nVidia, using 20 sparse matrices as a benchmark suite, the experimental results show that our method obtains significant performance improvement over the best existing CSR-based SpMV algorithms. The source code of this work is downloadable at https://github.com/bhSPARSE/Benchmark_SpMV_using_CSRComment: 22 pages, 8 figures, Published at Parallel Computing (PARCO

A Survey on Thread-Level Speculation Techniques

Producción CientíficaThread-Level Speculation (TLS) is a promising technique that allows the parallel execution of sequential code without relying on a prior, compile-time-dependence analysis. In this work, we introduce the technique, present a taxonomy of TLS solutions, and summarize and put into perspective the most relevant advances in this field.MICINN (Spain) and ERDF program of the European Union: HomProg-HetSys project (TIN2014-58876-P), CAPAP-H5 network (TIN2014-53522-REDT), and COST Program Action IC1305: Network for Sustainable Ultrascale Computing (NESUS)

A scalable architecture for ordered parallelism

We present Swarm, a novel architecture that exploits ordered irregular parallelism, which is abundant but hard to mine with current software and hardware techniques. In this architecture, programs consist of short tasks with programmer-specified timestamps. Swarm executes tasks speculatively and out of order, and efficiently speculates thousands of tasks ahead of the earliest active task to uncover ordered parallelism. Swarm builds on prior TLS and HTM schemes, and contributes several new techniques that allow it to scale to large core counts and speculation windows, including a new execution model, speculation-aware hardware task management, selective aborts, and scalable ordered commits. We evaluate Swarm on graph analytics, simulation, and database benchmarks. At 64 cores, Swarm achieves 51--122× speedups over a single-core system, and out-performs software-only parallel algorithms by 3--18×.National Science Foundation (U.S.) (Award CAREER-145299

Energy Implications of Photonic Networks With Speculative Transmission

Speculative transmission has been proposed to overcome the high latency of setting up end-to-end paths through photonic networks for computer systems. However, speculative transmission has implications for the energy efficiency of the network, in particular, control circuits are more complex and power hungry and failed speculative transmissions must be repeated. Moreover, in future chip multiprocessors (CMPs) with integrated photonic network end points, a large proportion of the additional energy will be dissipated on the CMP. This paper compares the energy characteristics of scheduled and speculative chip-to-chip networks for shared memory computer systems on the scale of a rack. For this comparison, we use a novel speculative control plane which reduces energy consumption by eliminating duplicate packets from the allocation process. In addition, we consider photonic power gating to reduce processor chip energy dissipation and the energy impact of the choice between semiconductor optical amplifier and ring resonator switching technologies. We model photonic network elements using values from the published literature as well as determine the power consumption of the allocator and network adapter circuits, implemented in a commercial low leakage 45 nm CMOS process. The power dissipated on the CMP using speculative networks is shown to be roughly double that of scheduled networks at saturation load and an order of magnitude higher at low loads

Implicit transactional memory in kilo-instruction multiprocessors

Although they have been the main server technology for many years, multiprocessors are undergoing a renaissance due to multi-core chips and the attractive scalability properties of combining a number of such multi-core chips into a system. The widespread use of multiprocessor systems will make performance losses due to consistency models and synchronization styles of popular programming models even more evident than they already are. Known architectural approaches to combat these losses are generally too complex, too specialized, or not transparent to software. In this article, we introduce implicit transactional memory as a generalized architectural concept to remove unnecessary performance losses caused by consistency models and synchronization styles. We show how the concept of implicit transactions can be implemented with low complexity by leveraging the multi-checkpoint mechanism of the Kilo-Instruction Processor. By relying on a general speculation substrate, this method supports even the strictest consistency model – sequential consistency – potentially as effectively as weaker models and it allows multiple threads to speculatively execute critical sections, beyond barriers and event synchronizations.Postprint (published version

Multiplex: Unifying Conventional and Speculative Thread-Level Parallelism on a Chip Multiprocessor

Recent proposals for Chip Multiprocessors (CMPs) advocate speculative, or implicit, threading in which the hardware employs prediction to peel off instruction sequences (i.e., implicit threads) from the sequential execution stream and speculatively executes them in parallel on multiple processor cores. These proposals augment a conventional multiprocessor, which employs explicit threading, with the ability to handle implicit threads. Current proposals focus on only implicitly-threaded code sections. This paper identifies, for the first time, the issues in combining explicit and implicit threading. We present the Multiplex architecture to combine the two threading models. Multiplex exploits the similarities between implicit and explicit threading, and provides a unified support for the two threading models without additional hardware. Multiplex groups a subset of protocol states in an implicitly-threaded CMP to provide a write-invalidate protocol for explicit threads. Using a fully-integrated compiler inf rastructure for automatic generation of Multiplex code, this paper presents a detailed performance analysis for entire benchmarks, instead of just implicitly- threaded sections, as done in previous papers. We show that neither threading models alone performs consistently better than the other across the benchmarks. A CMP with four dual-issue CPUs achieves a speedup of 1.48 and 2.17 over one dual-issue CPU, using implicit-only and explicit-only threading, respectively. Multiplex matches or outperforms the better of the two threading models for every benchmark, and a four-CPU Multiplex achieves a speedup of 2.63. Our detailed analysis indicates that the dominant overheads in an implicitly-threaded CMP are speculation state overflow due to limited L1 cache capacity, and load imbalance and data dependences in fine-grain threads