The Experts below are selected from a list of 25050 Experts worldwide ranked by ideXlab platform
Philippas Tsigas - One of the best experts on this subject based on the ideXlab platform.
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reading many variables in one Atomic Operation solutions with linear or sublinear complexity
IEEE Transactions on Parallel and Distributed Systems, 1994Co-Authors: Lefteris M Kirousis, Paul G Spirakis, Philippas TsigasAbstract:We address the problem of reading several variables (components) X/sub 1/,...,X/sub c/, all in one Atomic Operation, by only one process, called the reader, while each of these variables are being written by a set of writers. All Operations (i.e., both reads and writes) are assumed to be totally asynchronous and wait-free. For this problem, only algorithms that require at best quadratic time and space complexity can be derived from the existing literature. (The time complexity of a construction is the number of subOperations of a high-level Operation and its space complexity is the number of Atomic shared variables it needs) In this paper, we provide a deterministic protocol that has linear (in the number of processes) space complexity, linear time complexity for a read Operation, and constant time complexity for a write. Our solution does not make use of time-stamps. Rather, it is the memory location where a write writes that differentiates it from the other writes. Also, introducing randomness in the location where the reader gets the value that it returns, we get a conceptually very simple probabilistic algorithm. This algorithm has an overwhelmingly small, controllable probability of error. Its space complexity, and also the time complexity of a read Operation, are sublinear. The time complexity of a write is constant. On the other hand, under the Archimedean time assumption, we get a protocol whose time and space complexity do not depend on the number of writers, but are linear in the number of components only. (The time complexity of a write Operation is still constant.). >
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reading many variables in one Atomic Operation solutions with linear or sublinear complexity
International Workshop on Distributed Algorithms, 1991Co-Authors: Lefteris M Kirousis, Paul G Spirakis, Philippas TsigasAbstract:We address the problem of reading more than one variables (components) X1,..., Xc, all in one Atomic Operation, by a process called the reader, while each of these variables are being written by a set of writers. All Operations (i.e. both reads and writes) are assumed to be totally asynchronous and wait-free. The previous algorithms for this problem require at best quadratic time and space complexity (the time complexity of a construction is the number of sub-Operations of a high-level Operation and its space complexity is the number of Atomic shared variables it needs). We provide a (deterministic) solution which has linear (in the number of processes) space complexity, linear time complexity for a read Operation and constant time complexity for a write. Our solution does not make use of time-stamps. Rather, it is the memory location where a write writes that differentiates it from the other writes. Now, introducing randomness in the location where a reader gets the value it returns, we get a conceptually very simple probabilistic algorithm. This is the first probabilistic algorithm for the problem. Its space complexity as well as the time complexity of a read Operation are both sublinear. The time complexity of a write is still constant. On the other hand, under the Archimedean assumption, we get a protocol whose both time and space complexity do not depend on the number of writers but are linear in the number of components only (the time complexity of a write Operation is still constant).
Lefteris M Kirousis - One of the best experts on this subject based on the ideXlab platform.
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reading many variables in one Atomic Operation solutions with linear or sublinear complexity
IEEE Transactions on Parallel and Distributed Systems, 1994Co-Authors: Lefteris M Kirousis, Paul G Spirakis, Philippas TsigasAbstract:We address the problem of reading several variables (components) X/sub 1/,...,X/sub c/, all in one Atomic Operation, by only one process, called the reader, while each of these variables are being written by a set of writers. All Operations (i.e., both reads and writes) are assumed to be totally asynchronous and wait-free. For this problem, only algorithms that require at best quadratic time and space complexity can be derived from the existing literature. (The time complexity of a construction is the number of subOperations of a high-level Operation and its space complexity is the number of Atomic shared variables it needs) In this paper, we provide a deterministic protocol that has linear (in the number of processes) space complexity, linear time complexity for a read Operation, and constant time complexity for a write. Our solution does not make use of time-stamps. Rather, it is the memory location where a write writes that differentiates it from the other writes. Also, introducing randomness in the location where the reader gets the value that it returns, we get a conceptually very simple probabilistic algorithm. This algorithm has an overwhelmingly small, controllable probability of error. Its space complexity, and also the time complexity of a read Operation, are sublinear. The time complexity of a write is constant. On the other hand, under the Archimedean time assumption, we get a protocol whose time and space complexity do not depend on the number of writers, but are linear in the number of components only. (The time complexity of a write Operation is still constant.). >
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reading many variables in one Atomic Operation solutions with linear or sublinear complexity
International Workshop on Distributed Algorithms, 1991Co-Authors: Lefteris M Kirousis, Paul G Spirakis, Philippas TsigasAbstract:We address the problem of reading more than one variables (components) X1,..., Xc, all in one Atomic Operation, by a process called the reader, while each of these variables are being written by a set of writers. All Operations (i.e. both reads and writes) are assumed to be totally asynchronous and wait-free. The previous algorithms for this problem require at best quadratic time and space complexity (the time complexity of a construction is the number of sub-Operations of a high-level Operation and its space complexity is the number of Atomic shared variables it needs). We provide a (deterministic) solution which has linear (in the number of processes) space complexity, linear time complexity for a read Operation and constant time complexity for a write. Our solution does not make use of time-stamps. Rather, it is the memory location where a write writes that differentiates it from the other writes. Now, introducing randomness in the location where a reader gets the value it returns, we get a conceptually very simple probabilistic algorithm. This is the first probabilistic algorithm for the problem. Its space complexity as well as the time complexity of a read Operation are both sublinear. The time complexity of a write is still constant. On the other hand, under the Archimedean assumption, we get a protocol whose both time and space complexity do not depend on the number of writers but are linear in the number of components only (the time complexity of a write Operation is still constant).
Changyou Zhang - One of the best experts on this subject based on the ideXlab platform.
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sssp on gpu without Atomic Operation
International Conference on Human Centered Computing, 2016Co-Authors: Feng Wang, Liehuang Zhu, Changyou ZhangAbstract:Graph is a general theoretical model in many large scale data-driven applications. SSSP Single Source Shortest Path algorithm is a foundation for most important algorithms and applications. GPU remains its mainstream station in high performance computing with heterogeneous architecture computers. Because of the high parallelization of the GPU threads, the distances of the vertices of the GPU are updated by Atomic Operations to avoid the read and write errors. Most Atomic Operations are unnecessary since the read-write conflicts are rare in large graph. However, without Atomic Operations the result accuracy can't be guaranteed. The Atomic Operations take large part of the running time of the program. To improve the performance of SSSP on GPU, we proposed an algorithm with data block iterations instead of Atomic Operations. The algorithm not only gets a high speed-up but also guarantees the accuracy of the result. Experimental results show that this SSSP algorithm gained a speedup of three times than the serial algorithm on CPU and more than ten times than the parallel algorithm on GPU with Atomic Operation.
Paul G Spirakis - One of the best experts on this subject based on the ideXlab platform.
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reading many variables in one Atomic Operation solutions with linear or sublinear complexity
IEEE Transactions on Parallel and Distributed Systems, 1994Co-Authors: Lefteris M Kirousis, Paul G Spirakis, Philippas TsigasAbstract:We address the problem of reading several variables (components) X/sub 1/,...,X/sub c/, all in one Atomic Operation, by only one process, called the reader, while each of these variables are being written by a set of writers. All Operations (i.e., both reads and writes) are assumed to be totally asynchronous and wait-free. For this problem, only algorithms that require at best quadratic time and space complexity can be derived from the existing literature. (The time complexity of a construction is the number of subOperations of a high-level Operation and its space complexity is the number of Atomic shared variables it needs) In this paper, we provide a deterministic protocol that has linear (in the number of processes) space complexity, linear time complexity for a read Operation, and constant time complexity for a write. Our solution does not make use of time-stamps. Rather, it is the memory location where a write writes that differentiates it from the other writes. Also, introducing randomness in the location where the reader gets the value that it returns, we get a conceptually very simple probabilistic algorithm. This algorithm has an overwhelmingly small, controllable probability of error. Its space complexity, and also the time complexity of a read Operation, are sublinear. The time complexity of a write is constant. On the other hand, under the Archimedean time assumption, we get a protocol whose time and space complexity do not depend on the number of writers, but are linear in the number of components only. (The time complexity of a write Operation is still constant.). >
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reading many variables in one Atomic Operation solutions with linear or sublinear complexity
International Workshop on Distributed Algorithms, 1991Co-Authors: Lefteris M Kirousis, Paul G Spirakis, Philippas TsigasAbstract:We address the problem of reading more than one variables (components) X1,..., Xc, all in one Atomic Operation, by a process called the reader, while each of these variables are being written by a set of writers. All Operations (i.e. both reads and writes) are assumed to be totally asynchronous and wait-free. The previous algorithms for this problem require at best quadratic time and space complexity (the time complexity of a construction is the number of sub-Operations of a high-level Operation and its space complexity is the number of Atomic shared variables it needs). We provide a (deterministic) solution which has linear (in the number of processes) space complexity, linear time complexity for a read Operation and constant time complexity for a write. Our solution does not make use of time-stamps. Rather, it is the memory location where a write writes that differentiates it from the other writes. Now, introducing randomness in the location where a reader gets the value it returns, we get a conceptually very simple probabilistic algorithm. This is the first probabilistic algorithm for the problem. Its space complexity as well as the time complexity of a read Operation are both sublinear. The time complexity of a write is still constant. On the other hand, under the Archimedean assumption, we get a protocol whose both time and space complexity do not depend on the number of writers but are linear in the number of components only (the time complexity of a write Operation is still constant).
Feng Wang - One of the best experts on this subject based on the ideXlab platform.
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sssp on gpu without Atomic Operation
International Conference on Human Centered Computing, 2016Co-Authors: Feng Wang, Liehuang Zhu, Changyou ZhangAbstract:Graph is a general theoretical model in many large scale data-driven applications. SSSP Single Source Shortest Path algorithm is a foundation for most important algorithms and applications. GPU remains its mainstream station in high performance computing with heterogeneous architecture computers. Because of the high parallelization of the GPU threads, the distances of the vertices of the GPU are updated by Atomic Operations to avoid the read and write errors. Most Atomic Operations are unnecessary since the read-write conflicts are rare in large graph. However, without Atomic Operations the result accuracy can't be guaranteed. The Atomic Operations take large part of the running time of the program. To improve the performance of SSSP on GPU, we proposed an algorithm with data block iterations instead of Atomic Operations. The algorithm not only gets a high speed-up but also guarantees the accuracy of the result. Experimental results show that this SSSP algorithm gained a speedup of three times than the serial algorithm on CPU and more than ten times than the parallel algorithm on GPU with Atomic Operation.