We are implementing a pure IPv6 networking stack optimized to run on IoT endpoints connected to a network through an Ethernet interface. Our implementation supports only the minimal set of protocols required to enable efficient UDP-based communication. In particular, it does not include support for specialized operations such as multicasting, routing, load balancing, firewalling, network address translation, and tunneling. We are on track soon to release our network stack implementation.

Communication latencies within critical sections constitute a major bottleneck in some classes of emerging parallel workloads. In this paper, we argue for the use of Inferentially Queued Locks (IQLs) [31], not just for efficient synchronization but also for reducing communication latencies, and we propose a novel mechanism, Speculative Push (SP), aimed at reducing these communication latencies. With IQLs, the processor infers the existence, and limits, of a critical section from the use of synchronization instructions and joins a queue of lock requestors. The SP mechanism extracts information about program structure by observing IQLs. SP allows the cache controller, responding to a request for a cache line that likely includes a lock variable, to predict the data sets the requestor will modify within the associated critical section. The controller then pushes these lines from its own cache to the target cache, as well as writing them to memory. Overlapping the protected data transfer with that of the lock can substantially reduce the communication latencies within critical sections. By pushing data in exclusive state, the mechanism can collapse a read-modify-write sequences within a critical section into a single local cache access. The write-back to memory allows the receiving cache to ignore the push. Neither mechanism requires any programmer or compiler support nor any instruction set changes. Our experiments demonstrate that IQLs and SP can improve performance of applications employing frequent synchronization.

Efficiency of synchronization mechanisms can limit the parallel performance of many shared-memory applications. In addition, the ever increasing performance gap between processor and interprocessor communication may further compromise the scalability of these primitives. Ideally, synchronization primitives should provide high performance under both high and low contention without requiring substantial programmer effort and software support. QOLR has been shown to offer substantial speedups and to outperform other synchronization primitives consistently, but at the cost of software support and protocol complexity. This paper proposes the use of speculation and delays to implement a purely hardware-based queueing mechanism called Implicit QOLB. Making use of the pervasiveness of the Load-Linked/Store-Conditional primitives, we present a series of hardware mechanisms to optimize performance for sharing patterns exhibited by locks and associated data. The mechanisms do not require any change to existing software or instruction sets. IQOLB sits alongside the cache-coherence protocol and guides the decisions the protocol makes with respect to lock (and associated data) transfers. Preliminary evaluations indicate that IQOLB may perform as well as, if not better than, QOLB without the additional software and protocol complexity.

Efficient synchronization primitives are essential for achieving high performance in fine-grain, shared-memory parallel programs. One function of synchronization primitives is to enable exclusive access to shared data and critical sections of code. This paper makes three contributions. (1) We enumerate the five sources of overhead that locking synchronization primitives can incur. (2) We describe four mechanisms (local spinning, queue-based locking, collocation, and synchronized prefetch) that reduce these synchronization overheads. (3) With detailed simulations, we show the extent to which these four mechanisms can improve the performance of shared-memory programs. We evaluate the space of these mechanisms using seventeen synchronization constructs, which are formed from six base typed of locks (TEST&SET, TEST&TEST&SET, MCS, LH, M, and QOLB). We show that large performance gains (speedups of more than 1.5 for three of five benchmarks) can be achieved if at least three optimizing mechanisms are used simultaneously. We find that QOLB, which incorporates all four mechanisms, outperforms all other primitives (including reactive synchronization) in all cases. Finally, we demonstrate the superior performance of a low-cost implementation of QOLB, which runs on an unmodified cluster of commodity workstations.

This paper makes the case that pin bandwidth will be a critical consideration for future microprocessors. We show that many of the techniques used to tolerate growing memory latencies do so at the expense of increased bandwidth requirements. Using a decomposition of execution time, we show that for modern processors that employ aggressive memory latency tolerance techniques, wasted cycles due to insufficient bandwidth generally exceed those due to raw memory latencies. Given the importance of maximizing memory bandwidth, we calculate effective pin bandwidth, then estimate optimal effective pin bandwidth. We measure these quantities by determining the amount by which both caches and minimal-traffic caches filter accesses to the lower levels of the memory hierarchy. We see that there is a gap that can exceed two orders of magnitude between the total memory traffic generated by caches and the minimal-traffic caches---implying that the potential exists to increase effective pin bandwidth substantially. We decompose this traffic gap into four factors, and show they contribute quite differently to traffic reduction for different benchmarks. We conclude that, in the short term, pin bandwidth limitations will make more complex on-chip caches cost-effective. For example, flexible caches may allow individual applications to choose from a range of caching policies. In the long term, we predict that off-chip accesses will be so expensive that all system memory will reside on one or more processor chips.

The jine-grain nature of shared-memory multiprocessor communication introduces overheads that can be substantial.Using the Scalable Coherent Inte~ace (SCI) as a base hardware platform and the SPLASH benchmark suite for applications, we analyze three techniques to reduce this overhead: (i) ejicient synchronization primitives, and in particular a hardware primitive called QOLB; (ii) weakened memory ordering constraints; and (iii) optimization of the cache-coherence protocol for two nodes sharing data.We per-jorrn simulations both for current technology and technology that we anticipate will be available jive years hence.We find that QOLB (of which this study perjorms thejirst detailed simulations)shows a large and consistent improvement, much larger than that predicted by Mellor-Crummey and Scott [19].The relaxation of memory ordering constraints also provides a consistent performance improvement.In accordance with prior results, we show that a more aggressive memory model produces more substantial performance improvements.The optimization for twonode sharing shows mixed results, correlating unsurprisingly with the presence of that sharing pattern in an application.Our most important results are (i) that the overheads eliminated with these optimization are largely orthogonal-the peiforrnance gains from supporting multiple optimization concurrently are for the most part additive-and(ii) that technological improvements increase both these overheads and the success of the optimization at reducing them.