Pub Date : 2008-10-31DOI: 10.1109/CLUSTR.2008.4663750
T. Newhall, D. Amato, A. Pshenichkin
We present reliability solutions for adaptable network RAM systems running on general-purpose clusters. Network RAM allows nodes with over-committed memory to swap pages over the network, storing them in the idle RAM of other nodes and avoiding swapping to slow, local disk. An adaptable network RAM system adjusts the amount of RAM currently available for storing remotely swapped pages in response to changes in nodespsila local RAM usage. It is important that network RAM systems provide reliability for remotely swapped page data. Without reliability, a single node failure can result in failure of unrelated processes running on other nodes by losing their remotely swapped pages. Adaptable network RAM systems pose extra difficulties in providing reliability because each nodepsilas capacity for storing remotely swapped pages changes over time, and because pages may move from node to node in response to these changes. Our novel dynamic RAID-based reliability solutions use idle RAM for storing page and reliability data, avoiding using slow disk for reliability. They are designed to work with the adaptive nature of our network RAM system (Nswap), allowing page and reliability data to migrate from node to node and allowing pages to be added to or removed from different parity groups. Additionally, page recovery runs concurrently with cluster applications, so that cluster applications do not have to wait until all data from a failed node is recovered before resuming execution. We present results comparing Nswap to disk swapping for a set of benchmarks running on our gigabit cluster. Our results show that reliable Nswap is up to 32 times faster than swapping to disk, and that there is virtually no impact on the performance of applications as they run concurrently with page recovery.
{"title":"Reliable adaptable Network RAM","authors":"T. Newhall, D. Amato, A. Pshenichkin","doi":"10.1109/CLUSTR.2008.4663750","DOIUrl":"https://doi.org/10.1109/CLUSTR.2008.4663750","url":null,"abstract":"We present reliability solutions for adaptable network RAM systems running on general-purpose clusters. Network RAM allows nodes with over-committed memory to swap pages over the network, storing them in the idle RAM of other nodes and avoiding swapping to slow, local disk. An adaptable network RAM system adjusts the amount of RAM currently available for storing remotely swapped pages in response to changes in nodespsila local RAM usage. It is important that network RAM systems provide reliability for remotely swapped page data. Without reliability, a single node failure can result in failure of unrelated processes running on other nodes by losing their remotely swapped pages. Adaptable network RAM systems pose extra difficulties in providing reliability because each nodepsilas capacity for storing remotely swapped pages changes over time, and because pages may move from node to node in response to these changes. Our novel dynamic RAID-based reliability solutions use idle RAM for storing page and reliability data, avoiding using slow disk for reliability. They are designed to work with the adaptive nature of our network RAM system (Nswap), allowing page and reliability data to migrate from node to node and allowing pages to be added to or removed from different parity groups. Additionally, page recovery runs concurrently with cluster applications, so that cluster applications do not have to wait until all data from a failed node is recovered before resuming execution. We present results comparing Nswap to disk swapping for a set of benchmarks running on our gigabit cluster. Our results show that reliable Nswap is up to 32 times faster than swapping to disk, and that there is virtually no impact on the performance of applications as they run concurrently with page recovery.","PeriodicalId":198768,"journal":{"name":"2008 IEEE International Conference on Cluster Computing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115401184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-10-31DOI: 10.1109/CLUSTR.2008.4663761
Wei Huang, Matthew J. Koop, D. Panda
Efficient intra-node shared memory communication is important for high performance computing (HPC), especially with the emergence of multi-core architectures. As clusters continue to grow in size and complexity, the use of virtual machine (VM) technologies has been suggested to ease the increasing number of management issues. As demonstrated by earlier research, shared memory communication must be optimized for VMs to attain the native-level performance required by HPC centers. In this paper, we enhance intra-node shared memory communication for VM environments. We propose a one-copy approach. Instead of following the traditional approach used in most MPI implementations, copying data in and out of a pre-allocated shared memory region, our approach dynamically maps user buffers between VMs, allowing data to be directly copied to its destination. We also propose a grant/mapping cache to reduce expensive buffer mapping cost in VM environment. We integrate this approach into MVAPICH2, our implementation of MPI-2 library. For intra-node communication, we are able to reduce the large message latency in VM-based environments by up to 35%, and increase bandwidth by up to 38% even as compared with unmodified MVAPICH2 running in a native environment. Evaluation with the NAS Parallel Benchmarks suite shows up to 15% improvement.
{"title":"Efficient one-copy MPI shared memory communication in Virtual Machines","authors":"Wei Huang, Matthew J. Koop, D. Panda","doi":"10.1109/CLUSTR.2008.4663761","DOIUrl":"https://doi.org/10.1109/CLUSTR.2008.4663761","url":null,"abstract":"Efficient intra-node shared memory communication is important for high performance computing (HPC), especially with the emergence of multi-core architectures. As clusters continue to grow in size and complexity, the use of virtual machine (VM) technologies has been suggested to ease the increasing number of management issues. As demonstrated by earlier research, shared memory communication must be optimized for VMs to attain the native-level performance required by HPC centers. In this paper, we enhance intra-node shared memory communication for VM environments. We propose a one-copy approach. Instead of following the traditional approach used in most MPI implementations, copying data in and out of a pre-allocated shared memory region, our approach dynamically maps user buffers between VMs, allowing data to be directly copied to its destination. We also propose a grant/mapping cache to reduce expensive buffer mapping cost in VM environment. We integrate this approach into MVAPICH2, our implementation of MPI-2 library. For intra-node communication, we are able to reduce the large message latency in VM-based environments by up to 35%, and increase bandwidth by up to 38% even as compared with unmodified MVAPICH2 running in a native environment. Evaluation with the NAS Parallel Benchmarks suite shows up to 15% improvement.","PeriodicalId":198768,"journal":{"name":"2008 IEEE International Conference on Cluster Computing","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123895157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-10-31DOI: 10.1109/CLUSTR.2008.4663765
Josep M. Pérez, Rosa M. Badia, Jesús Labarta
Parallel programming on SMP and multi-core architectures is hard. In this paper we present a programming model for those environments based on automatic function level parallelism that strives to be easy, flexible, portable, and performant. Its main trait is its ability to exploit task level parallelism by analyzing task dependencies at run time. We present the programming environment in the context of algorithms from several domains and pinpoint its benefits compared to other approaches. We discuss its execution model and its scheduler. Finally we analyze its performance and demonstrate that it offers reasonable performance without tuning, and that it can rival highly tuned libraries with minimal tuning effort.
{"title":"A dependency-aware task-based programming environment for multi-core architectures","authors":"Josep M. Pérez, Rosa M. Badia, Jesús Labarta","doi":"10.1109/CLUSTR.2008.4663765","DOIUrl":"https://doi.org/10.1109/CLUSTR.2008.4663765","url":null,"abstract":"Parallel programming on SMP and multi-core architectures is hard. In this paper we present a programming model for those environments based on automatic function level parallelism that strives to be easy, flexible, portable, and performant. Its main trait is its ability to exploit task level parallelism by analyzing task dependencies at run time. We present the programming environment in the context of algorithms from several domains and pinpoint its benefits compared to other approaches. We discuss its execution model and its scheduler. Finally we analyze its performance and demonstrate that it offers reasonable performance without tuning, and that it can rival highly tuned libraries with minimal tuning effort.","PeriodicalId":198768,"journal":{"name":"2008 IEEE International Conference on Cluster Computing","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124855699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-10-31DOI: 10.1109/CLUSTR.2008.4663780
H. Midorikawa, M. Kurokawa, R. Himeno, M. Sato
Emerging 64 bitOSpsilas supply a huge amount of memory address space that is essential for new applications using very large data. It is expected that the memory in connected nodes can be used to store swapped pages efficiently, especially in a dedicated cluster which has a high-speed network such as 10 GbE and Infiniband. In this paper, we propose the distributed large memory system (DLM), which provides very large virtual memory by using remote memory distributed over the nodes in a cluster. The performance of DLM programs using remote memory is compared to ordinary programs using local memory. The results of STREAM, NPB and Himeno benchmarks show that the DLM achieves better performance than other remote paging schemes using a block swap device to access remote memory. In addition to performance, DLM offers the advantages of easy availability and high portability, because it is a user-level software without the need for special hardware. To obtain high performance, the DLM can tune its parameters independently from kernel swap parameters. We also found that DLMpsilas independence of kernel swapping provides more stable behavior.
新兴的64位ospsilas提供了大量的内存地址空间，这对于使用非常大的数据的新应用程序是必不可少的。预计连接节点中的内存可以用于有效地存储交换页面，特别是在具有高速网络(如10gbe和Infiniband)的专用集群中。本文提出了分布式大内存系统(distributed large memory system, DLM)，它通过使用分布在集群节点上的远程内存来提供非常大的虚拟内存。将使用远程内存的DLM程序的性能与使用本地内存的普通程序进行比较。STREAM、NPB和Himeno基准测试的结果表明，DLM比使用块交换设备访问远程内存的其他远程分页方案实现了更好的性能。除了性能之外，DLM还提供了易于获得和高可移植性的优点，因为它是一种用户级软件，不需要特殊的硬件。为了获得高性能，DLM可以独立于内核交换参数调优其参数。我们还发现，内核交换的DLMpsilas独立性提供了更稳定的行为。
{"title":"DLM: A distributed Large Memory System using remote memory swapping over cluster nodes","authors":"H. Midorikawa, M. Kurokawa, R. Himeno, M. Sato","doi":"10.1109/CLUSTR.2008.4663780","DOIUrl":"https://doi.org/10.1109/CLUSTR.2008.4663780","url":null,"abstract":"Emerging 64 bitOSpsilas supply a huge amount of memory address space that is essential for new applications using very large data. It is expected that the memory in connected nodes can be used to store swapped pages efficiently, especially in a dedicated cluster which has a high-speed network such as 10 GbE and Infiniband. In this paper, we propose the distributed large memory system (DLM), which provides very large virtual memory by using remote memory distributed over the nodes in a cluster. The performance of DLM programs using remote memory is compared to ordinary programs using local memory. The results of STREAM, NPB and Himeno benchmarks show that the DLM achieves better performance than other remote paging schemes using a block swap device to access remote memory. In addition to performance, DLM offers the advantages of easy availability and high portability, because it is a user-level software without the need for special hardware. To obtain high performance, the DLM can tune its parameters independently from kernel swap parameters. We also found that DLMpsilas independence of kernel swapping provides more stable behavior.","PeriodicalId":198768,"journal":{"name":"2008 IEEE International Conference on Cluster Computing","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132565255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-10-13DOI: 10.1109/CLUSTR.2008.4663787
Bogdan Nicolae, Gabriel Antoniu, L. Bougé
We consider the problem of efficiently managing massive data in a large-scale distributed environment. We consider data strings of size in the order of Terabytes, shared and accessed by concurrent clients. On each individual access, a segment of a string, of the order of Megabytes, is read or modified. Our goal is to provide the clients with efficient fine-grain access the data string as concurrently as possible, without locking the string itself. This issue is crucial in the context of applications in the field of astronomy, databases, data mining and multimedia. We illustrate these requirements with the case of an application for searching supernovae. Our solution relies on distributed, RAM-based data storage, while leveraging a DHT-based, parallel metadata management scheme. The proposed architecture and algorithms have been validated through a software prototype and evaluated in a cluster environment.
{"title":"Enabling lock-free concurrent fine-grain access to massive distributed data: Application to supernovae detection","authors":"Bogdan Nicolae, Gabriel Antoniu, L. Bougé","doi":"10.1109/CLUSTR.2008.4663787","DOIUrl":"https://doi.org/10.1109/CLUSTR.2008.4663787","url":null,"abstract":"We consider the problem of efficiently managing massive data in a large-scale distributed environment. We consider data strings of size in the order of Terabytes, shared and accessed by concurrent clients. On each individual access, a segment of a string, of the order of Megabytes, is read or modified. Our goal is to provide the clients with efficient fine-grain access the data string as concurrently as possible, without locking the string itself. This issue is crucial in the context of applications in the field of astronomy, databases, data mining and multimedia. We illustrate these requirements with the case of an application for searching supernovae. Our solution relies on distributed, RAM-based data storage, while leveraging a DHT-based, parallel metadata management scheme. The proposed architecture and algorithms have been validated through a software prototype and evaluated in a cluster environment.","PeriodicalId":198768,"journal":{"name":"2008 IEEE International Conference on Cluster Computing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125304478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we describe a whole-system live migration scheme, which transfers the whole system run-time state, including CPU state, memory data, and local disk storage, of the virtual machine (VM). To minimize the downtime caused by migrating large disk storage data and keep data integrity and consistency, we propose a three-phase migration (TPM) algorithm. To facilitate the migration back to initial source machine, we use an incremental migration (IM) algorithm to reduce the amount of the data to be migrated. Block-bitmap is used to track all the write accesses to the local disk storage during the migration. Synchronization of the local disk storage in the migration is performed according to the block-bitmap. Experiments show that our algorithms work well even when I/O-intensive workloads are running in the migrated VM. The downtime of the migration is around 100 milliseconds, close to shared-storage migration. Total migration time is greatly reduced using IM. The block-bitmap based synchronization mechanism is simple and effective. Performance overhead of recording all the writes on migrated VM is very low.
{"title":"Live and incremental whole-system migration of virtual machines using block-bitmap","authors":"Yingwei Luo, Binbin Zhang, Xiaolin Wang, Zhenlin Wang, Yifeng Sun, Haogang Chen","doi":"10.1109/CLUSTR.2008.4663760","DOIUrl":"https://doi.org/10.1109/CLUSTR.2008.4663760","url":null,"abstract":"In this paper, we describe a whole-system live migration scheme, which transfers the whole system run-time state, including CPU state, memory data, and local disk storage, of the virtual machine (VM). To minimize the downtime caused by migrating large disk storage data and keep data integrity and consistency, we propose a three-phase migration (TPM) algorithm. To facilitate the migration back to initial source machine, we use an incremental migration (IM) algorithm to reduce the amount of the data to be migrated. Block-bitmap is used to track all the write accesses to the local disk storage during the migration. Synchronization of the local disk storage in the migration is performed according to the block-bitmap. Experiments show that our algorithms work well even when I/O-intensive workloads are running in the migrated VM. The downtime of the migration is around 100 milliseconds, close to shared-storage migration. Total migration time is greatly reduced using IM. The block-bitmap based synchronization mechanism is simple and effective. Performance overhead of recording all the writes on migrated VM is very low.","PeriodicalId":198768,"journal":{"name":"2008 IEEE International Conference on Cluster Computing","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114804069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-09-01DOI: 10.1109/CLUSTR.2008.4663751
Liting Hu, Hai Jin, Xiaofei Liao, Xianjie Xiong, Haikun Liu
The concept of green computing has attracted much attention recently in cluster computing. However, previous local approaches focused on saving the energy cost of the components in a single workstation without a global vision on the whole cluster, so it achieved undesirable power reduction effect. Other cluster-wide energy saving techniques could only be applied to homogeneous workstations and specific applications. This paper describes the design and implementation of a novel approach that uses live migration of virtual machines to transfer load among the nodes on a multilayer ring-based overlay. This scheme can reduce the power consumption greatly by regarding all the cluster nodes as a whole. Plus, it can be applied to both the homogeneous and heterogeneous servers. Experimental measurements show that the new method can reduce the power consumption by 74.8% over base at most with certain adjustably acceptable overhead. The effectiveness and performance insights are also analytically verified.
{"title":"Magnet: A novel scheduling policy for power reduction in cluster with virtual machines","authors":"Liting Hu, Hai Jin, Xiaofei Liao, Xianjie Xiong, Haikun Liu","doi":"10.1109/CLUSTR.2008.4663751","DOIUrl":"https://doi.org/10.1109/CLUSTR.2008.4663751","url":null,"abstract":"The concept of green computing has attracted much attention recently in cluster computing. However, previous local approaches focused on saving the energy cost of the components in a single workstation without a global vision on the whole cluster, so it achieved undesirable power reduction effect. Other cluster-wide energy saving techniques could only be applied to homogeneous workstations and specific applications. This paper describes the design and implementation of a novel approach that uses live migration of virtual machines to transfer load among the nodes on a multilayer ring-based overlay. This scheme can reduce the power consumption greatly by regarding all the cluster nodes as a whole. Plus, it can be applied to both the homogeneous and heterogeneous servers. Experimental measurements show that the new method can reduce the power consumption by 74.8% over base at most with certain adjustably acceptable overhead. The effectiveness and performance insights are also analytically verified.","PeriodicalId":198768,"journal":{"name":"2008 IEEE International Conference on Cluster Computing","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122861785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-09-01DOI: 10.1109/CLUSTR.2008.4663788
E. Brunet, François Trahay, Alexandre Denis
The current trend in clusters architecture leads toward a massive use of multicore chips. This hardware evolution raises bottleneck issues at the network interface level. The use of multiple parallel networks allows to overcome this problem as it provides an higher aggregate bandwidth. But this bandwidth remains theoretical as only a few communication libraries are able to exploit multiple networks. In this paper, we present an optimization strategy for the NEWMADELEINE communication library. This strategy is able to efficiently exploit parallel interconnect links. By sampling each networkpsilas capabilities, it is possible to estimate a transfer duration a priori. Splitting messages and sending chunks of messages over parallel links can thus be performed efficiently to reach the theoretical aggregate bandwidth. NEWMADELEINE is multithreaded and exploits multicore chips to send small packets, that involve CPU-consuming copies, in parallel.
{"title":"A multicore-enabled multirail communication engine","authors":"E. Brunet, François Trahay, Alexandre Denis","doi":"10.1109/CLUSTR.2008.4663788","DOIUrl":"https://doi.org/10.1109/CLUSTR.2008.4663788","url":null,"abstract":"The current trend in clusters architecture leads toward a massive use of multicore chips. This hardware evolution raises bottleneck issues at the network interface level. The use of multiple parallel networks allows to overcome this problem as it provides an higher aggregate bandwidth. But this bandwidth remains theoretical as only a few communication libraries are able to exploit multiple networks. In this paper, we present an optimization strategy for the NEWMADELEINE communication library. This strategy is able to efficiently exploit parallel interconnect links. By sampling each networkpsilas capabilities, it is possible to estimate a transfer duration a priori. Splitting messages and sending chunks of messages over parallel links can thus be performed efficiently to reach the theoretical aggregate bandwidth. NEWMADELEINE is multithreaded and exploits multicore chips to send small packets, that involve CPU-consuming copies, in parallel.","PeriodicalId":198768,"journal":{"name":"2008 IEEE International Conference on Cluster Computing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126766888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-09-01DOI: 10.1109/CLUSTR.2008.4663796
John Cavazos
The industry is now in agreement that the future of architecture design lies in multiple cores. As a consequence, all computer systems today, from embedded devices to petascale computing systems, are being developed using multicore processors. Although researchers in industry and academia are exploring many different multicore hardware design choices, most agree that developing portable software that achieves high performance on multicore processors is a major unsolved problem. We now see a plethora of architectural features, with little consensus on how the computation, memory, and communication structures in multicore systems will be organized. The wide disparity in hardware systems available has made it nearly impossible to write code that is portable in functionality while still taking advantage of the performance potential of each system. In this paper, we propose exploring the viability of developing intelligent compilers, focusing on key components that will allow application portability while still achieving high performance.
{"title":"Intelligent compilers","authors":"John Cavazos","doi":"10.1109/CLUSTR.2008.4663796","DOIUrl":"https://doi.org/10.1109/CLUSTR.2008.4663796","url":null,"abstract":"The industry is now in agreement that the future of architecture design lies in multiple cores. As a consequence, all computer systems today, from embedded devices to petascale computing systems, are being developed using multicore processors. Although researchers in industry and academia are exploring many different multicore hardware design choices, most agree that developing portable software that achieves high performance on multicore processors is a major unsolved problem. We now see a plethora of architectural features, with little consensus on how the computation, memory, and communication structures in multicore systems will be organized. The wide disparity in hardware systems available has made it nearly impossible to write code that is portable in functionality while still taking advantage of the performance potential of each system. In this paper, we propose exploring the viability of developing intelligent compilers, focusing on key components that will allow application portability while still achieving high performance.","PeriodicalId":198768,"journal":{"name":"2008 IEEE International Conference on Cluster Computing","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132346524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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