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The memory system is a major performance determinant for server processors. Ever-growing core counts and datasets demand higher memory bandwidth and capacity. DDR---the dominant processor interface to memory---requires a large number of on-chip pins, ...

Breadth-First Search (BFS) is a common building block for several graph processing algorithms today. In this work, we highlight that a large fraction of vertex visits across the network in distributed BFS results in wasteful work. We investigate methods ...

Key-Value Stores (KVS) are foundational infrastructure components for online services. Due to their latency-critical nature, today’s best-performing KVS contain a plethora of full-stack optimizations commonly targeting read-mostly, popularity-skewed ...

Datacenters have witnessed a staggering evolution in networking technologies, driven by insatiable application demands for larger datasets and inter-server data transfers. Modern NICs can already handle 100s of Gbps of traffic, a bandwidth capability ...

Resource management for geo-distributed infrastructures is challenging due to the scarcity and non-uniformity of edge resources, as well as the high client mobility and workload surges inherent to situation awareness applications. Due to their ...

A key challenge in programming crash-consistent applications for Persistent Memory (PM) is achieving high performance while controlling the order of PM updates. Managing persist ordering from the CPU typically requires frequent synchronization points, ...

The emerging paradigm of microservices decomposes online services into fine-grained software modules frequently communicating over the datacenter network, often using Remote Procedure Calls (RPCs). Ongoing advancements in the network stack have exposed ...

Network bandwidth demand in datacenters is doubling every 12 to 15 months. In response to this demand, high-bandwidth network interface cards, each capable of transferring 100s of Gigabits of data per second, are making inroads into the servers of next-...

When a computational task tolerates a relaxation of its specification or when an algorithm tolerates the effects of noise in its execution, hardware, system software, and programming language compilers or their runtime systems can trade deviations from ...

Large-scale online services are commonly structured as a network of software tiers, which communicate over the datacenter network using RPCs. Ongoing trends towards software decomposition have led to the prevalence of tiers receiving and generating RPCs ...

Datacenter operators have started deploying Persistent Memory (PM), leveraging its combination of fast access and persistence for significant performance gains. A key challenge for PM-aware software is to maintain high performance while achieving atomic ...

To provide low-latency and high-throughput guarantees, most large key-value stores keep the data in the memory of many servers. Despite the natural parallelism across lookups, the load imbalance, introduced by heavy skew in the popularity distribution ...

Modern online services come with stringent quality requirements in terms of response time tail latency. Because of their decomposition into fine-grained communicating software layers, a single user request fans out into a plethora of short, μs-scale ...

With emerging storage-class memory (SCM) nearing commercialization, there is evidence that it will deliver the much-anticipated high density and access latencies within only a few factors of DRAM. Nevertheless, the latency-sensitive nature of memory-...

With mainstream technologies to couple logic tightly with memory on the horizon, near-memory processing has re-emerged as a promising approach to improving performance and energy for data-centric computing. DRAM, however, is primarily designed for ...

The increasing demand for extracting value out of ever-growing data poses an ongoing challenge to system designers, a task only made trickier by the end of Dennard scaling. As the performance density of traditional CPU-centric architectures stagnates, ...

Modern in-memory services rely on large distributed object stores to achieve the high scalability essential to service thousands of requests concurrently. The independent and unpredictable nature of incoming requests results in random accesses to the ...

To provide low latency and high throughput guarantees, most large key-value stores keep the data in the memory of many servers. Despite the natural parallelism across lookups, the load imbalance, introduced by heavy skew in the popularity distribution ...

Despite the natural parallelism across lookups, performance of distributed key-value stores is often limited due to load imbalance induced by heavy skew in the popularity distribution of the dataset. To avoid violating service level objectives expressed ...

Datacenter operators rely on low-cost, high-density technologies to maximize throughput for data-intensive services with tight tail latencies. In-memory rack-scale computing is emerging as a promising paradigm in scale-out datacenters capitalizing on ...