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)

New data structures to handle speculative parallelization at runtime

Producción CientíficaSoftware-based, thread-level speculation (TLS) is a software technique that optimistically executes in parallel loops whose fully-parallel semantics can not be guaranteed at compile time. Modern TLS libraries allow to handle arbitrary data structures speculatively. This desired feature comes at the high cost of local store and/or remote recovery times: The easier the local store, the harder the remote recovery. Unfortunately, both times are on the critical path of any TLS system. In this paper we propose a solution that performs local store in constant time, while recover values in a time that is in the order of T, being T the number of threads. As we will see, this solution, together with some additional improvements, makes the difference between slowdowns and noticeable speedups in the speculative parallelization of non-synthetic, pointer-based applications on a real system. Our experimental results show a gain of 3.58× to 28× with respect to the baseline system, and a relative efficiency of up to, on average, 65 % with respect to a TLS implementation specifically tailored to the benchmarks used.Castilla-Leon Regional Government (VA172A12-2); Ministerio de Industria, Spain (CENIT OCEANLIDER); MICINN (Spain) and the European Union FEDER (MOGECOPP project TIN2011-25639, CAPAP-H3 net- work TIN2010-12011-E, CAPAP-H4 network TIN2011-15734-E)

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

Compiler-Driven Software Speculation for Thread-Level Parallelism

Current parallelizing compilers can tackle applications exercising regular access patterns on arrays or affine indices, where data dependencies can be expressed in a linear form. Unfortunately, there are cases that independence between statements of code cannot be guaranteed and thus the compiler conservatively produces sequential code. Programs that involve extensive pointer use, irregular access patterns, and loops with unknown number of iterations are examples of such cases. This limits the extraction of parallelism in cases where dependencies are rarely or never triggered at runtime. Speculative parallelism refers to methods employed during program execution that aim to produce a valid parallel execution schedule for programs immune to static parallelization. The motivation for this article is to review recent developments in the area of compiler-driven software speculation for thread-level parallelism and how they came about. The article is divided into two parts. In the first part the fundamentals of speculative parallelization for thread-level parallelism are explained along with a design choice categorization for implementing such systems. Design choices include the ways speculative data is handled, how data dependence violations are detected and resolved, how the correct data are made visible to other threads, or how speculative threads are scheduled. The second part is structured around those design choices providing the advances and trends in the literature with reference to key developments in the area. Although the focus of the article is in software speculative parallelization, a section is dedicated for providing the interested reader with pointers and references for exploring similar topics such as hardware thread-level speculation, transactional memory, and automatic parallelization

BFCA+: Automatic Synthesis of Parallel Code with TLS Capabilities

Producción CientíficaParallelization of sequential applications requires extracting information about the loops and how their variables are accessed, and afterwards, augmenting the source code with extra code depending on such information. In this paper we propose a framework that avoids such an error-prone, time-consuming task. Our solution leverages the compile-time information extracted from the source code to classify all variables used inside each loop according to their accesses. Then, our system, called BFCA+, automatically instruments the source code with the necessary OpenMP directives and clauses to allow its parallel execution, using the standard shared and private clauses for variable classification. The framework is also capable of instrumenting loops for speculative parallelization, with the help of the ATLaS runtime system, that defines a new speculative clause to point out those variables that may lead to a dependency violation. As a result, the target loop is guaranteed to correctly run in parallel, ensuring that its execution follows sequential semantics even in the presence of dependency violations. Our experimental evaluation shows that the framework not only saves development time, but also leads to a faster code than the one manually parallelized.MICINN (Spain) and ERDF program of the European Union: HomProg-HetSys project (TIN2014-58876-P), CAPAPH5 network (TIN2014-53522-REDT), and COST Program Action IC1305: Network for Sustainable Ultrascale Computing (NESUS)

Improving the Perfomance of a Pointer-Based, Speculative Parallelization Scheme

La paralelización especulativa es una técnica que intenta extraer paralelismo de los bucles no paralelizables en tiempo de compilación. La idea subyacente es ejecutar el código de forma optimista mientras un subsistema comprueba que no se viole la semántica secuencial. Han sido muchos los trabajos realizados en este campo, sin embargo, no conocemos ninguno que fuese capaz de paralelizar aplicaciones que utilizasen aritmética de punteros. En un trabajo previo del autor de esta memoria, se desarrolló una librería software capaz de soportar este tipo de aplicaciones. No obstante, el software desarrollado sufría de una limitación muy importante: el tiempo de ejecución de las versiones paralelas era mayor que el de las versiones secuenciales. A lo largo de este Trabajo de Fin de Máster, se aborda esta limitación, encontrando y corrigiendo las razones de esta falta de eficiencia, y situando el trabajo realizado en perspectiva, dentro de las contribuciones mundiales en este ámbito. Los resultados experimentales obtenidos con aplicaciones reales nos permiten afirmar que estas limitaciones han sido solventadas, ya que obtenemos speedups de hasta de un 1.61 . Así, con la nueva versión de la librería se han llegado a obtener mejoras de hasta el 421.4% respecto al tiempo de ejecución generado por la versión original de la librería especulativa.InformáticaMáster en Investigación en Tecnologías de la Información y las Comunicacione

Using the Xeon Phi platform to run speculatively-parallelized codes

Producción CientíficaIntel Xeon Phi accelerators are one of the newest devices used in the field of parallel computing. However, there are comparatively few studies concerning their performance when using most of the existing parallelization techniques. One of them is thread-level speculation, a technique that optimistically tries to extract parallelism of loops without the need of a compile-time analysis that guarantees that the loop can be executed in parallel. In this article we evaluate the performance delivered by an Intel Xeon Phi coprocessor when using a software, state-of-the-art thread-level speculative parallelization library in the execution of well-known benchmarks. We describe both the internal characteristics of the Xeon Phi platform and the particularities of the thread-level speculation library being used as benchmark. Our results show that, although the Xeon Phi delivers a relatively good speedup in comparison with a shared-memory architecture in terms of scalability, the relatively low computing power of its computational units when specific vectorization and SIMD instructions are not fully exploited makes this first generation of Xeon Phi architectures not competitive (in terms of absolute performance) with respect to conventional multicore systems for the execution of speculatively parallelized code.2018-04-01Castilla-Leon Regional Government (VA172A12-2); MICINN (Spain) and the European Union FEDER (MOGECOPP project TIN2011-25639, HomProg-HetSys project TIN2014-58876-P, CAPAP-H5 network TIN2014-53522-REDT)

An alternative optimization technique for JavaScript engines

ABSTRACT Thread Level Speculation at function level has been suggested as a method to automatically (or semi-automatically) extract parallelism from sequential programs. While there have been multiple implementations in both hardware and software, little work has been done in the context of dynamic programming languages such as JavaScript. In this paper we evaluate the effects of a simple Thread Level Speculation approach, implemented on top of the Rhino1 7R2 JavaScript engine. The evalauation is done using the wellknown JavaScript benchmark suite V8. More specifically, we have measured the effects of our null return value prediction approach for function calls, conflicts with variables in a global scope, and the effects on the execution time. The results show that our strategy to speculate on return values is successful, that conflicts with global variables occur, and for several applications are the execution time improved, while the performance decrease for some applications due to speculation overhead