The Experts below are selected from a list of 45 Experts worldwide ranked by ideXlab platform
M Kandemir - One of the best experts on this subject based on the ideXlab platform.
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provisioning a multi tiered Data Staging Area for extreme scale machines
International Conference on Distributed Computing Systems, 2011Co-Authors: Ramya Prabhakar, Sudharshan S Vazhkudai, Youngjae Kim, Ali R Butt, M KandemirAbstract:Massively parallel scientific applications, running on extreme-scale supercomputers, produce hundreds of terabytes of Data per run, driving the need for storage solutions to improve their I/O performance. Traditional parallel file systems (PFS) in high performance computing (HPC) systems are unable to keep up with such high Data rates, creating a storage wall. In this work, we present a novel multi-tiered storage architecture comprising hybrid node-local resources to construct a dynamic Data Staging Area for extreme-scale machines. Such a Staging ground serves as an impedance matching device between applications and the PFS. Our solution combines diverse resources (e.g., DRAM, SSD) in such a way as to approach the performance of the fastest component technology and the cost of the least expensive one. We have developed an automated provisioning algorithm that aids in meeting the check pointing performance requirement of HPC applications, by using a least-cost storage configuration. We evaluate our approach using both an implementation on a large scale cluster and a simulation driven by six-years worth of Jaguar supercomputer job-logs, and show that our approach, by choosing an appropriate storage configuration, achieves 41.5% cost savings with only negligible impact on performance.
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ICDCS - Provisioning a Multi-tiered Data Staging Area for Extreme-Scale Machines
2011 31st International Conference on Distributed Computing Systems, 2011Co-Authors: Ramya Prabhakar, Sudharshan S Vazhkudai, Youngjae Kim, Ali R Butt, M KandemirAbstract:Massively parallel scientific applications, running on extreme-scale supercomputers, produce hundreds of terabytes of Data per run, driving the need for storage solutions to improve their I/O performance. Traditional parallel file systems (PFS) in high performance computing (HPC) systems are unable to keep up with such high Data rates, creating a storage wall. In this work, we present a novel multi-tiered storage architecture comprising hybrid node-local resources to construct a dynamic Data Staging Area for extreme-scale machines. Such a Staging ground serves as an impedance matching device between applications and the PFS. Our solution combines diverse resources (e.g., DRAM, SSD) in such a way as to approach the performance of the fastest component technology and the cost of the least expensive one. We have developed an automated provisioning algorithm that aids in meeting the check pointing performance requirement of HPC applications, by using a least-cost storage configuration. We evaluate our approach using both an implementation on a large scale cluster and a simulation driven by six-years worth of Jaguar supercomputer job-logs, and show that our approach, by choosing an appropriate storage configuration, achieves 41.5% cost savings with only negligible impact on performance.
Ramya Prabhakar - One of the best experts on this subject based on the ideXlab platform.
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provisioning a multi tiered Data Staging Area for extreme scale machines
International Conference on Distributed Computing Systems, 2011Co-Authors: Ramya Prabhakar, Sudharshan S Vazhkudai, Youngjae Kim, Ali R Butt, M KandemirAbstract:Massively parallel scientific applications, running on extreme-scale supercomputers, produce hundreds of terabytes of Data per run, driving the need for storage solutions to improve their I/O performance. Traditional parallel file systems (PFS) in high performance computing (HPC) systems are unable to keep up with such high Data rates, creating a storage wall. In this work, we present a novel multi-tiered storage architecture comprising hybrid node-local resources to construct a dynamic Data Staging Area for extreme-scale machines. Such a Staging ground serves as an impedance matching device between applications and the PFS. Our solution combines diverse resources (e.g., DRAM, SSD) in such a way as to approach the performance of the fastest component technology and the cost of the least expensive one. We have developed an automated provisioning algorithm that aids in meeting the check pointing performance requirement of HPC applications, by using a least-cost storage configuration. We evaluate our approach using both an implementation on a large scale cluster and a simulation driven by six-years worth of Jaguar supercomputer job-logs, and show that our approach, by choosing an appropriate storage configuration, achieves 41.5% cost savings with only negligible impact on performance.
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ICDCS - Provisioning a Multi-tiered Data Staging Area for Extreme-Scale Machines
2011 31st International Conference on Distributed Computing Systems, 2011Co-Authors: Ramya Prabhakar, Sudharshan S Vazhkudai, Youngjae Kim, Ali R Butt, M KandemirAbstract:Massively parallel scientific applications, running on extreme-scale supercomputers, produce hundreds of terabytes of Data per run, driving the need for storage solutions to improve their I/O performance. Traditional parallel file systems (PFS) in high performance computing (HPC) systems are unable to keep up with such high Data rates, creating a storage wall. In this work, we present a novel multi-tiered storage architecture comprising hybrid node-local resources to construct a dynamic Data Staging Area for extreme-scale machines. Such a Staging ground serves as an impedance matching device between applications and the PFS. Our solution combines diverse resources (e.g., DRAM, SSD) in such a way as to approach the performance of the fastest component technology and the cost of the least expensive one. We have developed an automated provisioning algorithm that aids in meeting the check pointing performance requirement of HPC applications, by using a least-cost storage configuration. We evaluate our approach using both an implementation on a large scale cluster and a simulation driven by six-years worth of Jaguar supercomputer job-logs, and show that our approach, by choosing an appropriate storage configuration, achieves 41.5% cost savings with only negligible impact on performance.
Youngjae Kim - One of the best experts on this subject based on the ideXlab platform.
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provisioning a multi tiered Data Staging Area for extreme scale machines
International Conference on Distributed Computing Systems, 2011Co-Authors: Ramya Prabhakar, Sudharshan S Vazhkudai, Youngjae Kim, Ali R Butt, M KandemirAbstract:Massively parallel scientific applications, running on extreme-scale supercomputers, produce hundreds of terabytes of Data per run, driving the need for storage solutions to improve their I/O performance. Traditional parallel file systems (PFS) in high performance computing (HPC) systems are unable to keep up with such high Data rates, creating a storage wall. In this work, we present a novel multi-tiered storage architecture comprising hybrid node-local resources to construct a dynamic Data Staging Area for extreme-scale machines. Such a Staging ground serves as an impedance matching device between applications and the PFS. Our solution combines diverse resources (e.g., DRAM, SSD) in such a way as to approach the performance of the fastest component technology and the cost of the least expensive one. We have developed an automated provisioning algorithm that aids in meeting the check pointing performance requirement of HPC applications, by using a least-cost storage configuration. We evaluate our approach using both an implementation on a large scale cluster and a simulation driven by six-years worth of Jaguar supercomputer job-logs, and show that our approach, by choosing an appropriate storage configuration, achieves 41.5% cost savings with only negligible impact on performance.
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ICDCS - Provisioning a Multi-tiered Data Staging Area for Extreme-Scale Machines
2011 31st International Conference on Distributed Computing Systems, 2011Co-Authors: Ramya Prabhakar, Sudharshan S Vazhkudai, Youngjae Kim, Ali R Butt, M KandemirAbstract:Massively parallel scientific applications, running on extreme-scale supercomputers, produce hundreds of terabytes of Data per run, driving the need for storage solutions to improve their I/O performance. Traditional parallel file systems (PFS) in high performance computing (HPC) systems are unable to keep up with such high Data rates, creating a storage wall. In this work, we present a novel multi-tiered storage architecture comprising hybrid node-local resources to construct a dynamic Data Staging Area for extreme-scale machines. Such a Staging ground serves as an impedance matching device between applications and the PFS. Our solution combines diverse resources (e.g., DRAM, SSD) in such a way as to approach the performance of the fastest component technology and the cost of the least expensive one. We have developed an automated provisioning algorithm that aids in meeting the check pointing performance requirement of HPC applications, by using a least-cost storage configuration. We evaluate our approach using both an implementation on a large scale cluster and a simulation driven by six-years worth of Jaguar supercomputer job-logs, and show that our approach, by choosing an appropriate storage configuration, achieves 41.5% cost savings with only negligible impact on performance.
Ali R Butt - One of the best experts on this subject based on the ideXlab platform.
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provisioning a multi tiered Data Staging Area for extreme scale machines
International Conference on Distributed Computing Systems, 2011Co-Authors: Ramya Prabhakar, Sudharshan S Vazhkudai, Youngjae Kim, Ali R Butt, M KandemirAbstract:Massively parallel scientific applications, running on extreme-scale supercomputers, produce hundreds of terabytes of Data per run, driving the need for storage solutions to improve their I/O performance. Traditional parallel file systems (PFS) in high performance computing (HPC) systems are unable to keep up with such high Data rates, creating a storage wall. In this work, we present a novel multi-tiered storage architecture comprising hybrid node-local resources to construct a dynamic Data Staging Area for extreme-scale machines. Such a Staging ground serves as an impedance matching device between applications and the PFS. Our solution combines diverse resources (e.g., DRAM, SSD) in such a way as to approach the performance of the fastest component technology and the cost of the least expensive one. We have developed an automated provisioning algorithm that aids in meeting the check pointing performance requirement of HPC applications, by using a least-cost storage configuration. We evaluate our approach using both an implementation on a large scale cluster and a simulation driven by six-years worth of Jaguar supercomputer job-logs, and show that our approach, by choosing an appropriate storage configuration, achieves 41.5% cost savings with only negligible impact on performance.
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ICDCS - Provisioning a Multi-tiered Data Staging Area for Extreme-Scale Machines
2011 31st International Conference on Distributed Computing Systems, 2011Co-Authors: Ramya Prabhakar, Sudharshan S Vazhkudai, Youngjae Kim, Ali R Butt, M KandemirAbstract:Massively parallel scientific applications, running on extreme-scale supercomputers, produce hundreds of terabytes of Data per run, driving the need for storage solutions to improve their I/O performance. Traditional parallel file systems (PFS) in high performance computing (HPC) systems are unable to keep up with such high Data rates, creating a storage wall. In this work, we present a novel multi-tiered storage architecture comprising hybrid node-local resources to construct a dynamic Data Staging Area for extreme-scale machines. Such a Staging ground serves as an impedance matching device between applications and the PFS. Our solution combines diverse resources (e.g., DRAM, SSD) in such a way as to approach the performance of the fastest component technology and the cost of the least expensive one. We have developed an automated provisioning algorithm that aids in meeting the check pointing performance requirement of HPC applications, by using a least-cost storage configuration. We evaluate our approach using both an implementation on a large scale cluster and a simulation driven by six-years worth of Jaguar supercomputer job-logs, and show that our approach, by choosing an appropriate storage configuration, achieves 41.5% cost savings with only negligible impact on performance.
Sudharshan S Vazhkudai - One of the best experts on this subject based on the ideXlab platform.
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provisioning a multi tiered Data Staging Area for extreme scale machines
International Conference on Distributed Computing Systems, 2011Co-Authors: Ramya Prabhakar, Sudharshan S Vazhkudai, Youngjae Kim, Ali R Butt, M KandemirAbstract:Massively parallel scientific applications, running on extreme-scale supercomputers, produce hundreds of terabytes of Data per run, driving the need for storage solutions to improve their I/O performance. Traditional parallel file systems (PFS) in high performance computing (HPC) systems are unable to keep up with such high Data rates, creating a storage wall. In this work, we present a novel multi-tiered storage architecture comprising hybrid node-local resources to construct a dynamic Data Staging Area for extreme-scale machines. Such a Staging ground serves as an impedance matching device between applications and the PFS. Our solution combines diverse resources (e.g., DRAM, SSD) in such a way as to approach the performance of the fastest component technology and the cost of the least expensive one. We have developed an automated provisioning algorithm that aids in meeting the check pointing performance requirement of HPC applications, by using a least-cost storage configuration. We evaluate our approach using both an implementation on a large scale cluster and a simulation driven by six-years worth of Jaguar supercomputer job-logs, and show that our approach, by choosing an appropriate storage configuration, achieves 41.5% cost savings with only negligible impact on performance.
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ICDCS - Provisioning a Multi-tiered Data Staging Area for Extreme-Scale Machines
2011 31st International Conference on Distributed Computing Systems, 2011Co-Authors: Ramya Prabhakar, Sudharshan S Vazhkudai, Youngjae Kim, Ali R Butt, M KandemirAbstract:Massively parallel scientific applications, running on extreme-scale supercomputers, produce hundreds of terabytes of Data per run, driving the need for storage solutions to improve their I/O performance. Traditional parallel file systems (PFS) in high performance computing (HPC) systems are unable to keep up with such high Data rates, creating a storage wall. In this work, we present a novel multi-tiered storage architecture comprising hybrid node-local resources to construct a dynamic Data Staging Area for extreme-scale machines. Such a Staging ground serves as an impedance matching device between applications and the PFS. Our solution combines diverse resources (e.g., DRAM, SSD) in such a way as to approach the performance of the fastest component technology and the cost of the least expensive one. We have developed an automated provisioning algorithm that aids in meeting the check pointing performance requirement of HPC applications, by using a least-cost storage configuration. We evaluate our approach using both an implementation on a large scale cluster and a simulation driven by six-years worth of Jaguar supercomputer job-logs, and show that our approach, by choosing an appropriate storage configuration, achieves 41.5% cost savings with only negligible impact on performance.
