From plasma to beefarm: Design experience of an FPGA-based multicore prototype

In this paper, we take a MIPS-based open-source uniprocessor soft core, Plasma, and extend it to obtain the Beefarm infrastructure for FPGA-based multiprocessor emulation, a popular research topic of the last few years both in the FPGA and the computer architecture communities. We discuss various design tradeoffs and we demonstrate superior scalability through experimental results compared to traditional software instruction set simulators. Based on our experience of designing and building a complete FPGA-based multiprocessor emulation system that supports run-time and compiler infrastructure and on the actual executions of our experiments running Software Transactional Memory (STM) benchmarks, we comment on the pros, cons and future trends of using hardware-based emulation for research.Peer ReviewedPostprint (author's final draft

Adaptive Transactional Memories: Performance and Energy Consumption Tradeoffs

Energy efficiency is becoming a pressing issue, especially in large data centers where it entails, at the same time, a non-negligible management cost, an enhancement of hardware fault probability, and a significant environmental footprint. In this paper, we study how Software Transactional Memories (STM) can provide benefits on both power saving and the overall applications’ execution performance. This is related to the fact that encapsulating shared-data accesses within transactions gives the freedom to the STM middleware to both ensure consistency and reduce the actual data contention, the latter having been shown to affect the overall power needed to complete the application’s execution. We have selected a set of self-adaptive extensions to existing STM middlewares (namely, TinySTM and R-STM) to prove how self-adapting computation can capture the actual degree of parallelism and/or logical contention on shared data in a better way, enhancing even more the intrinsic benefits provided by STM. Of course, this benefit comes at a cost, which is the actual execution time required by the proposed approaches to precisely tune the execution parameters for reducing power consumption and enhancing execution performance. Nevertheless, the results hereby provided show that adaptivity is a strictly necessary requirement to reduce energy consumption in STM systems: Without it, it is not possible to reach any acceptable level of energy efficiency at all

New hardware support transactional memory and parallel debugging in multicore processors

This thesis contributes to the area of hardware support for parallel programming by introducing new hardware elements in multicore processors, with the aim of improving the performance and optimize new tools, abstractions and applications related with parallel programming, such as transactional memory and data race detectors. Specifically, we configure a hardware transactional memory system with signatures as part of the hardware support, and we develop a new hardware filter for reducing the signature size. We also develop the first hardware asymmetric data race detector (which is also able to tolerate them), based also in hardware signatures. Finally, we propose a new module of hardware signatures that solves some of the problems that we found in the previous tools related with the lack of flexibility in hardware signatures

Towards lightweight and high-performance hardware transactional memory

Conventional lock-based synchronization serializes accesses to critical sections guarded by the same lock. Using multiple locks brings the possibility of a deadlock or a livelock in the program, making parallel programming a difficult task. Transactional Memory (TM) is a promising paradigm for parallel programming, offering an alternative to lock-based synchronization. TM eliminates the risk of deadlocks and livelocks, while it provides the desirable semantics of Atomicity, Consistency, and Isolation of critical sections. TM speculatively executes a series of memory accesses as a single, atomic, transaction. The speculative changes of a transaction are kept private until the transaction commits. If a transaction can break the atomicity or cause a deadlock or livelock, the TM system aborts the transaction and rolls back the speculative changes. To be effective, a TM implementation should provide high performance and scalability. While implementations of TM in pure software (STM) do not provide desirable performance, Hardware TM (HTM) implementations introduce much smaller overhead and have relatively good scalability, due to their better control of hardware resources. However, many HTM systems support only the transactions that fit limited hardware resources (for example, private caches), and fall back to software mechanisms if hardware limits are reached. These HTM systems, called best-effort HTMs, are not desirable since they force a programmer to think in terms of hardware limits, to use both HTM and STM, and to manage concurrent transactions in HTM and STM. In contrast with best-effort HTMs, unbounded HTM systems support overflowed transactions, that do not fit into private caches. Unbounded HTM systems often require complex protocols or expensive hardware mechanisms for conflict detection between overflowed transactions. In addition, an execution with overflowed transactions is often much slower than an execution that has only regular transactions. This is typically due to restrictive or approximative conflict management mechanism used for overflowed transactions. In this thesis, we study hardware implementations of transactional memory, and make three main contributions. First, we improve the general performance of HTM systems by proposing a scalable protocol for conflict management. The protocol has precise conflict detection, in contrast with often-employed inexact Bloom-filter-based conflict detection, which often falsely report conflicts between transactions. Second, we propose a best-effort HTM that utilizes the new scalable conflict detection protocol, termed EazyHTM. EazyHTM allows parallel commits for all non-conflicting transactions, and generally simplifies transaction commits. Finally, we propose an unbounded HTM that extends and improves the initial protocol for conflict management, and we name it EcoTM. EcoTM features precise conflict detection, and it efficiently supports large as well as small and short transactions. The key idea of EcoTM is to leverage an observation that very few locations are actually conflicting, even if applications have high contention. In EcoTM, each core locally detects if a cache line is non-conflicting, and conflict detection mechanism is invoked only for the few potentially conflicting cache lines.La Sincronización tradicional basada en los cerrojos de exclusión mutua (locks) serializa los accesos a las secciones críticas protegidas este cerrojo. La utilización de varios cerrojos en forma concurrente y/o paralela aumenta la posibilidad de entrar en abrazo mortal (deadlock) o en un bloqueo activo (livelock) en el programa, está es una de las razones por lo cual programar en forma paralela resulta ser mucho mas dificultoso que programar en forma secuencial. La memoria transaccional (TM) es un paradigma prometedor para la programación paralela, que ofrece una alternativa a los cerrojos. La memoria transaccional tiene muchas ventajas desde el punto de vista tanto práctico como teórico. TM elimina el riesgo de bloqueo mutuo y de bloqueo activo, mientras que proporciona una semántica de atomicidad, coherencia, aislamiento con características similares a las secciones críticas. TM ejecuta especulativamente una serie de accesos a la memoria como una transacción atómica. Los cambios especulativos de la transacción se mantienen privados hasta que se confirma la transacción. Si una transacción entra en conflicto con otra transacción o sea que alguna de ellas escribe en una dirección que la otra leyó o escribió, o se entra en un abrazo mortal o en un bloqueo activo, el sistema de TM aborta la transacción y revierte los cambios especulativos. Para ser eficaz, una implementación de TM debe proporcionar un alto rendimiento y escalabilidad. Las implementaciones de TM en el software (STM) no proporcionan este desempeño deseable, en cambio, las mplementaciones de TM en hardware (HTM) tienen mejor desempeño y una escalabilidad relativamente buena, debido a su mejor control de los recursos de hardware y que la resolución de los conflictos así el mantenimiento y gestión de los datos se hace en hardware. Sin embargo, muchos de los sistemas de HTM están limitados a los recursos de hardware disponibles, por ejemplo el tamaño de las caches privadas, y dependen de mecanismos de software para cuando esos límites son sobrepasados. Estos sistemas HTM, llamados best-effort HTM no son deseables, ya que obligan al programador a pensar en términos de los límites existentes en el hardware que se esta utilizando, así como en el sistema de STM que se llama cuando los recursos son sobrepasados. Además, tiene que resolver que transacciones hardware y software se ejecuten concurrentemente. En cambio, los sistemas de HTM ilimitados soportan un numero de operaciones ilimitadas o sea no están restringidos a límites impuestos artificialmente por el hardware, como ser el tamaño de las caches o buffers internos. Los sistemas HTM ilimitados por lo general requieren protocolos complejos o mecanismos muy costosos para la detección de conflictos y el mantenimiento de versiones de los datos entre las transacciones. Por otra parte, la ejecución de transacciones es a menudo mucho más lenta que en una ejecución sobre un sistema de HTM que este limitado. Esto es debido al que los mecanismos utilizados en el HTM limitado trabaja con conjuntos de datos relativamente pequeños que caben o están muy cerca del núcleo del procesador. En esta tesis estudiamos implementaciones de TM en hardware. Presentaremos tres contribuciones principales: Primero, mejoramos el rendimiento general de los sistemas, al proponer un protocolo escalable para la gestión de conflictos. El protocolo detecta los conflictos de forma precisa, en contraste con otras técnicas basadas en filtros Bloom, que pueden reportar conflictos falsos entre las transacciones. Segundo, proponemos un best-effort HTM que utiliza el nuevo protocolo escalable detección de conflictos, denominado EazyHTM. EazyHTM permite la ejecución completamente paralela de todas las transacciones sin conflictos, y por lo general simplifica la ejecución. Por último, proponemos una extensión y mejora del protocolo inicial para la gestión de conflictos, que llamaremos EcoTM. EcoTM cuenta con detección de conflictos precisa, eficiente y es compatible tanto con transacciones grandes como con pequeñas. La idea clave de EcoTM es aprovechar la observación que en muy pocas ubicaciones de memoria aparecen los conflictos entre las transacciones, incluso en aplicaciones tienen muchos conflictos. En EcoTM, cada núcleo detecta localmente si la línea es conflictiva, además existe un mecanismo de detección de conflictos detallado que solo se activa para las pocas líneas de memoria que son potencialmente conflictivas

A Safety-First Approach to Memory Models.

Sequential consistency (SC) is arguably the most intuitive behavior for a shared-memory multithreaded program. It is widely accepted that language-level SC could significantly improve programmability of a multiprocessor system. However, efficiently supporting end-to-end SC remains a challenge as it requires that both compiler and hardware optimizations preserve SC semantics. Current concurrent languages support a relaxed memory model that requires programmers to explicitly annotate all memory accesses that can participate in a data-race ("unsafe" accesses). This requirement allows compiler and hardware to aggressively optimize unannotated accesses, which are assumed to be data-race-free ("safe" accesses), while still preserving SC semantics. However, unannotated data races are easy for programmers to accidentally introduce and are difficult to detect, and in such cases the safety and correctness of programs are significantly compromised. This dissertation argues instead for a safety-first approach, whereby every memory operation is treated as potentially unsafe by the compiler and hardware unless it is proven otherwise. The first solution, DRFx memory model, allows many common compiler and hardware optimizations (potentially SC-violating) on unsafe accesses and uses a runtime support to detect potential SC violations arising from reordering of unsafe accesses. On detecting a potential SC violation, execution is halted before the safety property is compromised. The second solution takes a different approach and preserves SC in both compiler and hardware. Both SC-preserving compiler and hardware are also built on the safety-first approach. All memory accesses are treated as potentially unsafe by the compiler and hardware. SC-preserving hardware relies on different static and dynamic techniques to identify safe accesses. Our results indicate that supporting SC at the language level is not expensive in terms of performance and hardware complexity. The dissertation also explores an extension of this safety-first approach for data-parallel accelerators such as Graphics Processing Units (GPUs). Significant microarchitectural differences between CPU and GPU require rethinking of efficient solutions for preserving SC in GPUs. The proposed solution based on our SC-preserving approach performs nearly on par with the baseline GPU that implements a data-race-free-0 memory model.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120794/1/ansingh_1.pd

Improving redundant multithreading performance for soft-error detection in HPC applications

Tesis de Graduación (Maestría en Computación) Instituto Tecnológico de Costa Rica, Escuela de Computación, 2018As HPC systems move towards extreme scale, soft errors leading to silent data corruptions become a major concern. In this thesis, we propose a set of three optimizations to the classical Redundant Multithreading (RMT) approach to allow faster soft error detection. First, we leverage the use of Simultaneous Multithreading (SMT) to collocate sibling replicated threads on the same physical core to efficiently exchange data to expose errors. Some HPC applications cannot fully exploit SMT for performance improvement and instead, we propose to use these additional resources for fault tolerance. Second, we present variable aggregation to group several values together and use this merged value to speed up detection of soft errors. Third, we introduce selective checking to decrease the number of checked values to a minimum. The last two techniques reduce the overall performance overhead by relaxing the soft error detection scope. Our experimental evaluation, executed on recent multicore processors with representative HPC benchmarks, proves that the use of SMT for fault tolerance can enhance RMT performance. It also shows that, at constant computing power budget, with optimizations applied, the overhead of the technique can be significantly lower than the classical RMT replicated execution. Furthermore, these results show that RMT can be a viable solution for soft-error detection at extreme scale

Scalable, reliable, power-efficient communication for hardware transactional memory

Journal ArticleIn a hardware transactional memory system with lazy versioning and lazy conflict detection, the process of transaction commit can emerge as a bottleneck. This is especially true for a large-scale distributed memory system where multiple transactions may attempt to commit simultaneously and co-ordination is required before allowing commits to proceed in parallel. In this paper, we propose novel algorithms to implement commit that are more scalable (in terms of delay and energy) and are free of deadlocks/livelocks. We show that these algorithms have similarities with the token cache coherence concept and leverage these similarities to extend the algorithms to handle message loss and starvation scenarios. The proposed algorithms improve upon the state-of-the-art by yielding up to a 7X reduction in commit delay and up to a 48X reduction in network messages. These translate into overall performance improvements of up to 66% (for synthetic workloads with average transaction length of 200 cycles), 35% (for average transaction length of 1000 cycles), 8% (for average transaction length of 4000 cycles), and 41% (for a collection of SPLASH-2 programs)

Mechanisms for Unbounded, Conflict-Robust Hardware Transactional Memory

Conventional lock implementations serialize access to critical sections guarded by the same lock, presenting programmers with a difficult tradeoff between granularity of synchronization and amount of parallelism realized. Recently, researchers have been investigating an emerging synchronization mechanism called transactional memory as an alternative to such conventional lock-based synchronization. Memory transactions have the semantics of executing in isolation from one another while in reality executing speculatively in parallel, aborting when necessary to maintain the appearance of isolation. This combination of coarse-grained isolation and optimistic parallelism has the potential to ease the tradeoff presented by lock-based programming. This dissertation studies the hardware implementation of transactional memory, making three main contributions. First, we propose the permissions-only cache, a mechanism that efficiently increases the size of transactions that can be handled in the local cache hierarchy to optimize performance. Second, we propose OneTM, an unbounded hardware transactional memory system that serializes transactions that escape the local cache hierarchy. Finally, we propose RetCon, a novel mechanism for detecting conflicts that reduces conflicts by allowing transactions to commit with different values than those with which they executed as long as dataflow and control-flow constraints are maintained