Abstract. Memory isolation is a key property of a reliable and secure computing system -an access to one memory address should not have unintended side effects on data stored in other addresses. However, as DRAM process technology scales down to smaller dimensions, it becomes more difficult to prevent DRAM cells from electrically interacting with each other. In this paper, we expose the vulnerability of commodity DRAM chips to disturbance errors. By reading from the same address in DRAM, we show that it is possible to corrupt data in nearby addresses. More specifically, activating the same row in DRAM corrupts data in nearby rows. We demonstrate this phenomenon on Intel and AMD systems using a malicious program that generates many DRAM accesses. We induce errors in most DRAM modules (110 out of 129) from three major DRAM manufacturers. From this we conclude that many deployed systems are likely to be at risk. We identify the root cause of disturbance errors as the repeated toggling of a DRAM row's wordline, which stresses inter-cell coupling effects that accelerate charge leakage from nearby rows. We provide an extensive characterization study of disturbance errors and their behavior using an FPGA-based testing platform. Among our key findings, we show that (i) it takes as few as 139K accesses to induce an error and (ii) up to one in every 1.7K cells is susceptible to errors. After examining various potential ways of addressing the problem, we propose a low-overhead solution to prevent the errors.

As Chip Multiprocessors (CMPs) scale to tens or hundreds of nodes, the interconnect becomes a significant factor in cost, energy consumption and performance. Recent work has explored many design tradeoffs for networks-on-chip (NoCs) with novel router architectures to reduce hardware cost. In particular, recent work proposes bufferless deflection routing to eliminate router buffers. The high cost of buffers makes this choice potentially appealing, especially for lowto-medium network loads.However, current bufferless designs usually add complexity to control logic. Deflection routing introduces a sequential dependence in port allocation, yielding a slow critical path. Explicit mechanisms are required for livelock freedom due to the non-minimal nature of deflection. Finally, deflection routing can fragment packets, and the reassembly buffers require large worst-case sizing to avoid deadlock, due to the lack of network backpressure. The complexity that arises out of these three problems has discouraged practical adoption of bufferless routing.To counter this, we propose CHIPPER (Cheap-Interconnect Partially Permuting Router), a simplified router microarchitecture that eliminates in-router buffers and the crossbar. We introduce three key insights: first, that deflection routing port allocation maps naturally to a permutation network within the router; second, that livelock freedom requires only an implicit token-passing scheme, eliminating expensive age-based priorities; and finally, that flow control can provide correctness in the absence of network backpressure, avoiding deadlock and allowing cache miss buffers (MSHRs) to be used as reassembly buffers. Using multiprogrammed SPEC CPU2006, server, and desktop application workloads and SPLASH-2 multithreaded workloads, we achieve an average 54.9% network power reduction for 13.6% average performance degradation (multiprogrammed) and 73.4% power reduction for 1.9% slowdown (multithreaded), with minimal degradation and large power savings at low-to-medium load. Finally, we show 36.2% router area reduction relative to buffered routing, with comparable timing.

Energy efficiency and energy-proportional computing have become a central focus in enterprise server architecture. As thermal and electrical constraints limit system power, and datacenter operators become more conscious of energy costs, energy efficiency becomes important across the whole system. There are many proposals to scale energy at the datacenter and server level. However, one significant component of server power, the memory system, remains largely unaddressed. We propose memory dynamic voltage/frequency scaling (DVFS) to address this problem, and evaluate a simple algorithm in a real system.As we show, in a typical server platform, memory consumes 19% of system power on average while running SPEC CPU2006 workloads. While increasing core counts demand more bandwidth and drive the memory frequency upward, many workloads require much less than peak bandwidth. These workloads suffer minimal performance impact when memory frequency is reduced. When frequency reduces, voltage can be reduced as well. We demonstrate a large opportunity for memory power reduction with a simple control algorithm that adjusts memory voltage and frequency based on memory bandwidth utilization.We evaluate memory DVFS in a real system, emulating reduced memory frequency by altering timing registers and using an analytical model to compute power reduction. With an average of 0.17% slowdown, we show 10.4% average (20.5% max) memory power reduction, yielding 2.4% average (5.2% max) whole-system energy improvement.

A primary use of chip-multiprocessor (CMP) systems is to speed up a single application by exploiting thread-level parallelism. In such systems, threads may slow each other down by issuing memory requests that interfere in the shared memory subsystem. This inter-thread memory system interference can significantly degrade parallel application performance. Better memory request scheduling may mitigate such performance degradation. However, previously proposed memory scheduling algorithms for CMPs are designed for multi-programmed workloads where each core runs an independent application, and thus do not take into account the inter-dependent nature of threads in a parallel application.In this paper, we propose a memory scheduling algorithm designed specifically for parallel applications. Our approach has two main components, targeting two common synchronization primitives that cause inter-dependence of threads: locks and barriers. First, the runtime system estimates threads holding the locks that cause the most serialization as the set of limiter threads, which are prioritized by the memory scheduler. Second, the memory scheduler shuffles thread priorities to reduce the time threads take to reach the barrier. We show that our memory scheduler speeds up a set of memory-intensive parallel applications by 12.6% compared to the best previous memory scheduling technique.

A conventional Network-on-Chip (NoC) router uses input buffers to store in-flight packets. These buffers improve performance, but consume significant power. It is possible to bypass these buffers when they are empty, reducing dynamic power, but static buffer power, and dynamic power when buffers are utilized, remain. To improve energy efficiency, bufferless deflection routing removes input buffers, and instead uses deflection (misrouting) to resolve contention. However, at high network load, deflections cause unnecessary network hops, wasting power and reducing performance.In this work, we propose a new NoC router design called the minimally-buffered deflection (MinBD) router. This router combines deflection routing with a small "side buffer," which is much smaller than conventional input buffers. A MinBD router places some network traffic that would have otherwise been deflected in this side buffer, reducing deflections significantly. The router buffers only a fraction of traffic, thus making more efficient use of buffer space than a router that holds every flit in its input buffers. We evaluate MinBD against input-buffered routers of various sizes that implement buffer bypassing, a bufferless router, and a hybrid design, and show that MinBD is more energy-efficient than all prior designs, and has performance that approaches the conventional input-buffered router with area and power close to the bufferless router.

Several system-level operations trigger bulk data copy or initialization. Even though these bulk data operations do not require any computation, current systems transfer a large quantity of data back and forth on the memory channel to perform such operations. As a result, bulk data operations consume high latency, bandwidth, and energy-degrading both system performance and energy e ciency.In this work, we propose RowClone, a new and simple mechanism to perform bulk copy and initialization completely within DRAM -eliminating the need to transfer any data over the memory channel to perform such operations. Our key observation is that DRAM can internally and e ciently transfer a large quantity of data (multiple KBs) between a row of DRAM cells and the associated row bu er. Based on this, our primary mechanism can quickly copy an entire row of data from a source row to a destination row by rst copying the data from the source row to the row bu er and then from the row bu er to the destination row, via two back-to-back activate commands. This mechanism, which we call the Fast Parallel Mode of RowClone, reduces the latency and energy consumption of a 4KB bulk copy operation by 11.6x and 74.4x, respectively, and a 4KB bulk zeroing operation by 6.0x and 41.5x, respectively. To e ciently copy data between rows that do not share a row bu er, we propose a second mode of RowClone, the Pipelined Serial Mode, which uses the shared internal bus of a DRAM chip to quickly copy data between two banks. RowClone requires only a 0.01% increase in DRAM chip area.We quantitatively evaluate the bene ts of RowClone by focusing on fork, one of the frequently invoked system calls, and ve other copy and initialization intensive applications. Our results show that RowClone can signi cantly improve both single-core and multi-core system performance, while also signi cantly reducing main memory bandwidth and energy consumption.

Abstract-The network-on-chip (NoC) is a primary shared resource in a chip multiprocessor (CMP) system. As core counts continue to increase and applications become increasingly data-intensive, the network load will also increase, leading to more congestion in the network. This network congestion can degrade system performance if the network load is not appropriately controlled. Prior works have proposed sourcethrottling congestion control, which limits the rate at which new network traffic (packets) enters the NoC in order to reduce congestion and improve performance. These prior congestion control mechanisms have shortcomings that significantly limit their performance: either 1) they are not application-aware, but rather throttle all applications equally regardless of applications' sensitivity to latency, or 2) they are not network-loadaware, throttling according to application characteristics but sometimes under-or over-throttling the cores.In this work, we propose Heterogeneous Adaptive Throttling, or HAT, a new source-throttling congestion control mechanism based on two key principles: application-aware throttling and network-load-aware throttling rate adjustment. First, we observe that only network-bandwidth-intensive applications (those which use the network most heavily) should be throttled, allowing the other latency-sensitive applications to make faster progress without as much interference. Second, we observe that the throttling rate which yields the best performance varies between workloads; a single, static, throttling rate underthrottles some workloads while over-throttling others. Hence, the throttling mechanism should observe network load dynamically and adjust its throttling rate accordingly. While some past works have also used a closed-loop control approach, none have been application-aware. HAT is the first mechanism to combine application-awareness and network-load-aware throttling rate adjustment to address congestion in a NoC.We evaluate HAT using a wide variety of multiprogrammed workloads on several NoC-based CMP systems with 16-, 64-, and 144-cores and compare its performance to two state-ofthe-art congestion control mechanisms. Our evaluations show that HAT consistently provides higher system performance and fairness than prior congestion control mechanisms.

Abstract-Hierarchical ring networks, which hierarchically connect multiple levels of rings, have been proposed in the past to improve the scalability of ring interconnects, but past hierarchical ring designs sacrifice some of the key benefits of rings by reintroducing more complex in-ring buffering and buffered flow control. Our goal in this paper is to design a new hierarchical ring interconnect that can maintain most of the simplicity of traditional ring designs (i.e., no in-ring buffering or buffered flow control) while achieving high scalability as more complex buffered hierarchical ring designs.To this end, we revisit the concept of a hierarchical-ring networkon-chip. Our design, called HiRD (Hierarchical Rings with Deflection), includes critical features that enable us to mostly maintain the simplicity of traditional simple ring topologies while providing higher energy efficiency and scalability. First, HiRD does not have any buffering or buffered flow control within individual rings, and requires only a small amount of buffering between the ring hierarchy levels. When inter-ring buffers are full, our design simply deflects flits so that they circle the ring and try again, which eliminates the need for in-ring buffering. Second, we introduce two simple mechanisms that together provide an end-to-end delivery guarantee within the entire network (despite any deflections that occur) without impacting the critical path or latency of the vast majority of network traffic.Our experimental evaluations on a wide variety of multiprogrammed and multithreaded workloads and synthetic traffic patterns show that HiRD attains equal or better performance at better energy efficiency than multiple versions of both a previous hierarchical ring design and a traditional single ring design. We also extensively analyze our design's characteristics and injection and delivery guarantees. We conclude that HiRD can be a compelling design point that allows higher energy efficiency and scalability while retaining the simplicity and appeal of conventional ring-based designs.