Keval Vora
Keval Vora

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Bibliometrics: publication history
Average citations per article3.91
Citation Count43
Publication count11
Publication years2014-2017
Available for download8
Average downloads per article379.38
Downloads (cumulative)3,035
Downloads (12 Months)1,379
Downloads (6 Weeks)160
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11 results found Export Results: bibtexendnoteacmrefcsv

Result 1 – 11 of 11
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1 published by ACM
November 2017 IA3'17: Proceedings of the Seventh Workshop on Irregular Applications: Architectures and Algorithms
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 13,   Downloads (12 Months): 33,   Downloads (Overall): 33

Full text available: PDFPDF
Massive parallel processing power of GPUs has attracted researchers to develop iterative vertex-centric graph processing frameworks for GPUs. Enabling work-efficiency in these solutions, however, is not straightforward and comes at the cost of SIMD-inefficiency and load imbalance. This paper offers techniques that overcome these challenges when processing the graph on ...

2 published by ACM
April 2017 ASPLOS '17: Proceedings of the Twenty-Second International Conference on Architectural Support for Programming Languages and Operating Systems
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 40,   Downloads (12 Months): 299,   Downloads (Overall): 299

Full text available: PDFPDF
Continuous processing of a streaming graph maintains an approximate result of the iterative computation on a recent version of the graph. Upon a user query, the accurate result on the current graph can be quickly computed by feeding the approximate results to the iterative computation --- a form of incremental ...
Keywords: value dependence, graph processing, streaming graphs
Also published in:
May 2017  ACM SIGPLAN Notices - ASPLOS '17: Volume 52 Issue 4, April 2017 May 2017  ACM SIGARCH Computer Architecture News - Asplos'17: Volume 45 Issue 1, March 2017

3 published by ACM
April 2017 ASPLOS '17: Proceedings of the Twenty-Second International Conference on Architectural Support for Programming Languages and Operating Systems
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 29,   Downloads (12 Months): 240,   Downloads (Overall): 240

Full text available: PDFPDF
Existing distributed asynchronous graph processing systems employ checkpointing to capture globally consistent snapshots and rollback all machines to most recent checkpoint to recover from machine failures. In this paper we argue that recovery in distributed asynchronous graph processing does not require the entire execution state to be rolled back to ...
Keywords: fault tolerance, distributed processing, graph processing
Also published in:
May 2017  ACM SIGPLAN Notices - ASPLOS '17: Volume 52 Issue 4, April 2017 May 2017  ACM SIGARCH Computer Architecture News - Asplos'17: Volume 45 Issue 1, March 2017

4 published by ACM
October 2016 ACM Transactions on Architecture and Code Optimization (TACO): Volume 13 Issue 4, December 2016
Publisher: ACM
Bibliometrics:
Citation Count: 2
Downloads (6 Weeks): 13,   Downloads (12 Months): 160,   Downloads (Overall): 244

Full text available: PDFPDF
Evolving graph processing involves repeating analyses, which are often iterative, over multiple snapshots of the graph corresponding to different points in time. Since the snapshots of an evolving graph share a great number of vertices and edges, traditional approaches that process these snapshots one at a time without exploiting this ...
Keywords: Graph processing, temporal graphs, message aggregation

5
June 2016 USENIX ATC '16: Proceedings of the 2016 USENIX Conference on Usenix Annual Technical Conference
Publisher: USENIX Association
Bibliometrics:
Citation Count: 0

Single-PC, disk-based processing of big graphs has recently gained much popularity. At the core of an efficient disk-based system is a well-designed partition structure that can minimize random disk accesses. All existing systems use static partitions that are created before processing starts. These partitions have static layouts and are loaded ...

6 published by ACM
May 2016 HPDC '16: Proceedings of the 25th ACM International Symposium on High-Performance Parallel and Distributed Computing
Publisher: ACM
Bibliometrics:
Citation Count: 2
Downloads (6 Weeks): 11,   Downloads (12 Months): 135,   Downloads (Overall): 226

Full text available: PDFPDF
Large-scale parallel graph analytics involves executing iterative algorithms (e.g., PageRank, Shortest Paths, etc.) that are both data- and compute-intensive. In this work we construct faster versions of iterative graph algorithms from their original counterparts using input graph reduction. A large input graph is transformed into a small graph using a ...
Keywords: input reduction, iterative algorithms, graph processing

7 published by ACM
October 2015 OOPSLA 2015: Proceedings of the 2015 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 7,   Downloads (12 Months): 68,   Downloads (Overall): 176

Full text available: PDFPDF
Floating point representation has limited precision and inputs to floating point programs may also have errors. Consequently, during execution, errors are introduced, propagated, and accumulated, leading to unreliable outputs. We call this the instability problem. We propose RAIVE, a technique that identifies output variations of a floating point execution in ...
Keywords: instability, cancellation, vectorization, floating point representation
Also published in:
December 2015  ACM SIGPLAN Notices - OOPSLA '15: Volume 50 Issue 10, October 2015

8
September 2015 CLUSTER '15: Proceedings of the 2015 IEEE International Conference on Cluster Computing
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 1

Clusters with caching DSMs deliver programmability and performance by supporting shared-memory programming and tolerate remote I/O latencies via caching. The input to a data parallel program is partitioned across the cluster while the DSM transparently fetches and caches remote data as needed. Irregular applications, however, are challenging to parallelize because ...
Keywords: caching, directory protocol, distributed speculation, optimizations, piggybacking, early misspeculation detection, fast recovery

9 published by ACM
October 2014 OOPSLA '14: Proceedings of the 2014 ACM International Conference on Object Oriented Programming Systems Languages & Applications
Publisher: ACM
Bibliometrics:
Citation Count: 7
Downloads (6 Weeks): 8,   Downloads (12 Months): 104,   Downloads (Overall): 555

Full text available: PDFPDF
Many vertex-centric graph algorithms can be expressed using asynchronous parallelism by relaxing certain read-after-write data dependences and allowing threads to compute vertex values using stale (i.e., not the most recent) values of their neighboring vertices. We observe that on distributed shared memory systems, by converting synchronous algorithms into their asynchronous ...
Keywords: distributed shared memory, graph mining, pde solvers, communication latency, graph analytics, best effort refresh, bounded staleness
Also published in:
December 2014  ACM SIGPLAN Notices - OOPSLA '14: Volume 49 Issue 10, October 2014

10 published by ACM
June 2014 HPDC '14: Proceedings of the 23rd international symposium on High-performance parallel and distributed computing
Publisher: ACM
Bibliometrics:
Citation Count: 24
Downloads (6 Weeks): 39,   Downloads (12 Months): 340,   Downloads (Overall): 1,262

Full text available: PDFPDF
Vertex-centric graph processing is employed by many popular algorithms (e.g., PageRank) due to its simplicity and efficient use of asynchronous parallelism. The high compute power provided by SIMT architecture presents an opportunity for accelerating these algorithms using GPUs. Prior works of graph processing on a GPU employ Compressed Sparse Row ...
Keywords: coalesced memory accesses, g-shards, gpu, concatenated windows, graph representation

11
May 2014 IPDPSW '14: Proceedings of the 2014 IEEE International Parallel & Distributed Processing Symposium Workshops
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 1

Graph-based applications have become increasingly important in many application domains. The large graph sizes offer data level parallelism at a scale that makes it attractive to run such applications on distributed shared memory (DSM) based modern clusters composed of multicore machines. Our analysis of several graph applications that rely on ...
Keywords: Distributed Shared Memory, Clusters, Runtime Monitoring, Dynamic Adaptive Model, Speculative Parallelism, Asynchronous Parallelism



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