1,184 papers · page 23 of 60
Over the past two decades, many concurrent data structures have been designed and implemented. Nearly all such work analyzes concurrent data structures empirically, omitting asymptotic bounds on their efficiency, partly because of the complexity of the analysis needed, and partly…
Lock-free algorithms guarantee progress by having threads help one another. Complex lock-free operations facilitate helping by creating descriptor objects that describe how other threads should help them. In many lock-free algorithms, a new descriptor is allocated for each operat…
Availability of large data sets like ImageNet and massively parallel computation support in modern HPC devices like NVIDIA GPUs have fueled a renewed interest in Deep Learning (DL) algorithms. This has triggered the development of DL frameworks like Caffe, Torch, TensorFlow, and …
Synchronization and data movement are the key impediments to an efficient parallel execution. To ensure that data shared by multiple threads remain consistent, the programmer must use synchronization (e.g., mutex locks) to serialize threads' accesses to data. This limits parallel…
Modern big data processing platforms employ huge in-memory key-value (KV) maps. Their applications simultaneously drive high-rate data ingestion and large-scale analytics. These two scenarios expect KV-map implementations that scale well with both real-time updates and large atom…
We explore a programming approach for concurrency that synchronizes all accesses to shared memory by default. Synchronization takes place by ensuring that all program code runs inside atomic sections even if the program code has external side effects. Threads are mapped to atomic…
Nodes with multiple GPUs are becoming the platform of choice for high-performance computing. However, most applications are written using bulk-synchronous programming models, which may not be optimal for irregular algorithms that benefit from low-latency, asynchronous communicati…
In this work, we introduce and experimentally evaluate a new hybrid software-hardware Transactional Memory prototype based on Intel's Haswell TSX architecture. Our prototype extends the applicability of the existing hardware support for TM by interposing a hybrid fall-back layer …
The popularity of Non-Uniform Memory Access (NUMA) architectures has led to numerous locality-preserving hierarchical lock designs, such as HCLH, HMCS, and cohort locks. Locality-preserving locks trade fairness for higher throughput. Hence, some instances of acquisitions can incu…
Modern GPUs are broadly adopted in many multitasking environments, including data centers and smartphones. However, the current support for the scheduling of multiple GPU kernels (from different applications) is limited, forming a major barrier for GPU to meet many practical need…
Standard cache-oblivious recursive divide-and-conquer algorithms for evaluating dynamic programming recurrences have optimal serial cache complexity but often have lower parallelism compared with iterative wavefront algorithms due to artificial dependencies among subtasks. Very r…
State teleportation is a new technique for exploiting hardware transactional memory (HTM) to improve existing synchronization and memory management schemes for highly-concurrent data structures. When applied to fine-grained locking, a thread holding the lock for a node launches a…
Data-structures can benefit from dynamic data layout modifications when the size or the shape of the data structure changes during the execution, or when different phases in the program execute different workloads. However, in a modern multi-core environment, layout modifications…
Large-scale graphs are becoming critical in various domains such as social network, scientific application, knowledge discovery, and even system software, etc. Many of those use cases require large-scale high-performance graph databases, which are designed for serving continuous …
In distributed computing, parallel overheads such as \emph{synchronization overhead} may hinder performance. We introduce the idea of \emph{Distributed Control} (DC) where global synchronization is reduced to \emph{termination detection} and each worker proceeds ahead optimistica…
Finite State Machine (FSM) is the key kernel behind many popular applications, including regular expression matching, text tokenization, and Huffman decoding. Parallelizing FSMs is extremely difficult because of the strong dependencies and unpredictable memory accesses. Previous …
Semi-structured data emerge in many domains, especially in web analytics and business intelligence. However, querying such data is inherently sequential due to the nested structure of input data. Existing solutions pessimistically enumerate all execution paths to circumvent depen…
Various existing optimization and memory consistency management techniques for GPU applications rely on memory access patterns of kernels. However, they suffer from poor practicality because they require explicit user interventions to extract kernel memory access patterns. This p…
On modern multi-core processors, independent workloads often interfere with each other by competing for shared cache space. However, for multi-threaded workloads, where a single copy of data can be accessed by multiple threads, the threads can cooperatively share cache. Because d…
The current design trend in large scale machine learning is to use distributed clusters of CPUs and GPUs with MapReduce-style programming. Some have been led to believe that this type of horizontal scaling can reduce or even eliminate the need for traditional algorithm developmen…