1,184 papers · page 14 of 60
Aggressive technology scaling trends have worsened the transient fault problem in high-performance computing (HPC) systems. Some faults are benign, but others can lead to silent data corruption (SDC), which represents a serious problem; a fault introducing an error that is not re…
Sparse tensor contractions appear commonly in many applications. Efficiently computing a two sparse tensor product is challenging: It not only inherits the challenges from common sparse matrix-matrix multiplication (SpGEMM), i.e., indirect memory access and unknown output size be…
Fifty years of parallel programming has generated a substantial legacy parallel codebase, creating a new portability challenge: re-parallelizing already parallel code. Our solution exploits inherently portable parallel patterns, and addresses the challenge of identifying patterni…
Hypergraph partitioning is used in many problem domains including VLSI design, linear algebra, Boolean satisfiability, and data mining. Most versions of this problem are NP-complete or NP-hard, so practical hypergraph partitioners generate approximate partitioning solutions for a…
Binary code analysis is widely used to help assess a program's correctness, performance, and provenance. Binary analysis applications often construct control flow graphs, analyze data flow, and use debugging information to understand how machine code relates to source lines, inli…
Bundled references are a new building block to provide linearizable range query operations for highly concurrent linked data structures. They enable range queries to traverse a path through the data structure that is consistent with the target atomic snapshot. The path consists o…
Durable techniques coupled with transactional semantics provide to application developers the guarantee that data is saved consistently in persistent memory (PM), even in the event of a non-corrupting failure. Persistence fences and flush instructions are known to have a signific…
Manually optimizing the tradeoffs between accuracy, performance and energy for resource-intensive applications with flexible accuracy or precision requirements is extremely difficult. We present ApproxTuner, an automatic framework for accuracy-aware optimization of tensor-based a…
Many-to-many mapping models for user- to kernel-level threads (or "M:N threads") have been extensively studied for decades as a lightweight substitute for current Pthreads implementations that provide a simple one-to-one mapping ("1:1 threads"). M:N threads derive performance fro…
In-situ parallel workflows couple multiple component applications via streaming data transfer to avoid data exchange via shared file systems. Such workflows are challenging to configure for optimal performance due to the huge space of possible configurations. Here, we propose an …
Safe memory reclamation (SMR) algorithms suffer from a trade-off between bounding unreclaimed memory and the speed of reclamation. Hazard pointer (HP) based algorithms bound unreclaimed memory at all times, but tend to be slower than other approaches. Epoch based reclamation (EBR…
Nonblocking data structures face a safe memory reclamation (SMR) problem. In these algorithms, a node removed from the data structure cannot be reclaimed (freed) immediately, as other threads may be about to access it. The goal of an SMR scheme is to minimize the number of remove…
The lock-free, ordered, singly linked list as proposed in [5, 8] is a textbook example of a concurrent data structure [6, 10]. The data structure supports lock-free insertion and deletion, and wait-free contains operations on items identified by a unique key. The lock-free implem…
This paper presents a new Single Source Shortest Path (SSSP) algorithm for GPUs. Our key advancement is an improved work scheduler, which is central to the performance of SSSP algorithms. Previous GPU solutions for SSSP use simple work schedulers that can be implemented efficient…
Traversals are commonly seen in tree data structures, and performance-enhancing transformations between tree traversals are critical for many applications. Existing approaches to reasoning about tree traversals and their transformations are ad hoc, with various limitations on the…
Given a concurrent data structure, we present an approach for efficiently taking snapshots of its constituent CAS objects. More specifically, we support a constant-time operation that returns a snapshot handle. This snapshot handle can later be used to read the value of any base …
Dynamic memory management on GPUs is generally understood to be a challenging topic. On current GPUs, hundreds of thousands of threads might concurrently allocate new memory or free previously allocated memory. This leads to problems with thread contention, synchronization overhe…
Convolutional neural networks (CNNs), as representatives of deep learning, are one of the most commonly used neural networks in applications such as graphic image analysis. However, CNN has heavy computation patterns; network training processes could take several hours even with …
With the magnitude of graph-structured data continually increasing, graph processing systems that can scale-out and scale-up are needed to handle extreme-scale datasets. While existing distributed out-of-core solutions have made it possible, they suffer from limited performance d…
This paper investigates the problem of integrating two powerful abstractions for concurrent programming, namely futures and transactional memory. Our focus is on specifying the semantics of execution of "transactional futures", i.e., futures that execute as atomic transactions an…