Automatic Sharing Classification and Timely Push for Cache-coherent Systems

This paper proposes and evaluates Sharing/Timing Adaptive Push (STAP), a dynamic scheme for preemptively sending data from producers to consumers to minimize criticalpath communication latency. STAP uses small hardware buffers to dynamically detect sharing patterns and timing requirements. The scheme applies to both intra-node and inter-socket directorybased shared memory networks. We integrate STAP into a MOESI cache-coherence protocol using heuristics to detect different data sharing patterns, including broadcasts, producer/consumer, and migratory-data sharing. Using 12 benchmarks from the PARSEC and SPLASH-2 suites in 3 different configurations, we show that our scheme significantly reduces communication latency in NUMA systems and achieves an average of 10% performance improvement (up to 46%), with at most 2% on-chip storage overhead. When combined with existing prefetch schemes, STAP either outperforms prefetching or combines with prefetching for improved performance (up to 15% extra) in most cases

CROSS-LAYER CUSTOMIZATION FOR LOW POWER AND HIGH PERFORMANCE EMBEDDED MULTI-CORE PROCESSORS

Due to physical limitations and design difficulties, computer processor architecture has shifted to multi-core and even many-core based approaches in recent years. Such architectures provide potentials for sustainable performance scaling into future peta-scale/exa-scale computing platforms, at affordable power budget, design complexity, and verification efforts. To date, multi-core processor products have been replacing uni-core processors in almost every market segment, including embedded systems, general-purpose desktops and laptops, and super computers. However, many issues still remain with multi-core processor architectures that need to be addressed before their potentials could be fully realized. People in both academia and industry research community are still seeking proper ways to make efficient and effective use of these processors. The issues involve hardware architecture trade-offs, the system software service, the run-time management, and user application design, which demand more research effort into this field. Due to the architectural specialties with multi-core based computers, a Cross-Layer Customization framework is proposed in this work, which combines application specific information and system platform features, along with necessary operating system service support, to achieve exceptional power and performance efficiency for targeted multi-core platforms. Several topics are covered with specific optimization goals, including snoop cache coherence protocol, inter-core communication for producer-consumer applications, synchronization mechanisms, and off-chip memory bandwidth limitations. Analysis of benchmark program execution with conventional mechanisms is made to reveal the overheads in terms of power and performance. Specific customizations are proposed to eliminate such overheads with support from hardware, system software, compiler, and user applications. Experiments show significant improvement on system performance and power efficiency

The home-forwarding mechanism to reduce the cache coherence overhead in next-generation CMPs

On the road to computer systems able to support the requirements of exascale applications, Chip Multi-Processors (CMPs) are equipped with an ever increasing number of cores interconnected through fast on-chip networks. To exploit such new architectures, the parallel software must be able to scale almost linearly with the number of cores available. To this end, the overhead introduced by the run-time system of parallel programming frameworks and by the architecture itself must be small enough in order to enable high scalability also for very fine-grained parallel programs. An approach to reduce this overhead is to use non-conventional architectural mechanisms revealing useful when certain concurrency patterns in the running application are statically or dynamically recognized. Following this idea, this paper proposes a run-time support able to reduce the effective latency of inter-thread cooperation primitives by lowering the contention on individual caches. To achieve this goal, the new home-forwarding hardware mechanism is proposed and used by our runtime in order to reduce the amount of cache-to-cache interactions generated by the cache coherence protocol. Our ideas have been emulated on the Tilera TILEPro64 CMP, showing a significant speedup improvement in some first benchmarks

Store-Ordered Streaming of Shared Memory

Coherence misses in shared-memory multiprocessors account for a substantial fraction of execution time in many important scientific and commercial workloads. Memory streaming provides a promising solution to the coherence miss bottleneck because it improves memory level parallelism and lookahead while using on-chip resources efficiently. We observe that the order in which shared data are consumed by one processor is correlated to the order in which they were produced by another. We investigate this phenomenon and demonstrate that it can be exploited to send Store- ORDered Streams (SORDS) of shared data from producers to consumers, thereby eliminating coherent read misses. Using a trace-driven analysis of all user and OS memory references in a cache-coherent distributed shared- memory multiprocessor, we show that SORDS based memory streaming can eliminate between 36% and 100% of all coherent read misses in scientific workloads and between 23% and 48%in online transaction processing workloads

Selective, accurate, and timely self-invalidation using last-touch prediction

Communication in cache-coherent distributed shared memory (DSM) often requires invalidating (or writing back) cached copies of a memory block, incurring high overheads. This paper proposes Last-Touch Predictors (LTPs) that learn and predict the “last touch ” to a memory block by one processor before the block is accessed and subsequently invalidated by another. By predicting a last-touch and (self-)invalidating the block in advance, an LTP hides the invalidation time, significantly reducing the coherence overhead. The key behind accurate last-touch prediction is tracebased correlation, associating a last-touch with the sequence of instructions (i.e., a trace) touching the block from a coherence miss until the block is invalidated. Correlating instructions enables an LTP to identify a last-touch to a memory block uniquely throughout an application’s execution. In this paper, we use results from running shared-memory applications on a simulated DSM to evaluate LTPs. The results indicate that: (1) our base case LTP design, maintaining trace signatures on a per-block basis, substantially improves prediction accuracy over previous self-invalidation schemes to an average of 79%; (2) our alternative LTP design, maintaining a global trace signature table, reduces storage overhead but only achieves an average accuracy of 58%; (3) last-touch prediction based on a single instruction only achieves an average accuracy of 41 % due to instruction reuse within and across computation; and (4) LTP enables selective, accurate, and timely self-invalidation in DSM, speeding up program execution on average by 11%.

Predicting coherence communication by tracking synchronization points at run time.”

Abstract Predicting target processors that a coherence request must be delivered to can improve the miss handling latency in shared memory systems. In directory coherence protocols, directly communicating with the predicted processors avoids costly indirection to the directory. In snooping protocols, prediction relaxes the high bandwidth requirements by replacing broadcast with multicast. In this work, we propose a new run-time coherence target prediction scheme that exploits the inherent correlation between synchronization points in a program and coherence communication. Our workload-driven analysis shows that by exposing synchronization points to hardware and tracking them at run time, we can simply and effectively track stable and repetitive communication patterns. Based on this observation, we build a predictor that can improve the miss latency of a directory protocol by 13%. Compared with existing address-and instruction-based prediction techniques, our predictor achieves comparable performance using substantially smaller power and storage overheads