2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)最新文献_第3页

Message from the WAMCA 2020 General Chair 2020年WAMCA大会主席致辞

2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) Pub Date : 2020-09-01 DOI: 10.1109/sbac-pad49847.2020.00053

引用次数: 0

Analyzing the Loop Scheduling Mechanisms on Julia Multithreading Julia多线程的循环调度机制分析

2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) Pub Date : 2020-09-01 DOI: 10.1109/SBAC-PAD49847.2020.00043

Diana A. Barros, C. Bentes

引用次数: 2

High-Performance Low-Memory Lowering: GEMM-based Algorithms for DNN Convolution 高性能低内存降低:基于gem的DNN卷积算法

2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) Pub Date : 2020-09-01 DOI: 10.1109/SBAC-PAD49847.2020.00024

Andrew Anderson, Aravind Vasudevan, Cormac Keane, David Gregg

引用次数: 13

XPySom: High-Performance Self-Organizing Maps 高性能自组织映射

2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) Pub Date : 2020-09-01 DOI: 10.1109/SBAC-PAD49847.2020.00037

Riccardo Mancini, Antonio Ritacco, Giacomo Lanciano, T. Cucinotta

引用次数: 6

Selective Protection for Sparse Iterative Solvers to Reduce the Resilience Overhead 稀疏迭代求解器的选择性保护以减少弹性开销

2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) Pub Date : 2020-09-01 DOI: 10.1109/SBAC-PAD49847.2020.00029

Hongyang Sun, Ana Gainaru, Manu Shantharam, P. Raghavan

{"title":"Selective Protection for Sparse Iterative Solvers to Reduce the Resilience Overhead","authors":"Hongyang Sun, Ana Gainaru, Manu Shantharam, P. Raghavan","doi":"10.1109/SBAC-PAD49847.2020.00029","DOIUrl":"https://doi.org/10.1109/SBAC-PAD49847.2020.00029","url":null,"abstract":"The increasing scale and complexity of today's high-performance computing (HPC) systems demand a renewed focus on enhancing the resilience of long-running scientific applications in the presence of faults. Many of these applications are iterative in nature as they operate on sparse matrices that concern the simulation of partial differential equations (PDEs) which numerically capture the physical properties on discretized spatial domains. While these applications currently benefit from many application-agnostic resilience techniques at the system level, such as checkpointing and replication, there is significant overhead in deploying these techniques. In this paper, we seek to develop application-aware resilience techniques that leverage an iterative application's intrinsic resiliency to faults and selectively protect certain elements, thereby reducing the resilience overhead. Specifically, we investigate the impact of soft errors on the widely used Preconditioned Conjugate Gradient (PCG) method, whose reliability depends heavily on the error propagation through the sparse matrix-vector multiplication (SpMV) operation. By characterizing the performance of PCG in correlation with a numerical property of the underlying sparse matrix, we propose a selective protection scheme that protects only certain critical elements of the operation based on an analytical model. An experimental evaluation using 20 sparse matrices from the SuiteSparse Matrix Collection shows that our proposed scheme is able to reduce the resilience overhead by as much as 70.2% and an average of 32.6% compared to the baseline techniques with full-protection or zero-protection.","PeriodicalId":202581,"journal":{"name":"2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121317829","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}

引用次数: 2

Towards Profile-Guided Optimization for Safe and Efficient Parallel Stream Processing in Rust 面向Rust安全高效并行流处理的剖面导向优化

2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) Pub Date : 2020-09-01 DOI: 10.1109/SBAC-PAD49847.2020.00047

Stefan Sydow, Mohannad Nabelsee, S. Glesner, Paula Herber

{"title":"Towards Profile-Guided Optimization for Safe and Efficient Parallel Stream Processing in Rust","authors":"Stefan Sydow, Mohannad Nabelsee, S. Glesner, Paula Herber","doi":"10.1109/SBAC-PAD49847.2020.00047","DOIUrl":"https://doi.org/10.1109/SBAC-PAD49847.2020.00047","url":null,"abstract":"The efficient mapping of stream processing applications to parallel hardware architectures is a difficult problem. While parallelization is often highly desirable as it reduces the overall execution time, its advantages must be carefully weighed against the parallelization overhead of complexity and communication costs. This paper presents a novel profile-guided optimization for parallel stream processing based on the multi-paradigm system programming language Rust. Our approach's key idea is to systematically balance the performance gain that can be achieved from parallelization with the communication overhead. To achieve this, we 1) use profiling to gain tight estimates of task execution times, 2) evaluate the cost of the fundamental concurrency constructs in Rust with synthetic benchmarks, and exploit this information to estimate the communication overhead introduced by various degrees of parallelism, and 3) present a novel optimization algorithm that exploits both estimates to fine-tune the degree of parallelism and train processing in a given application. Overall, our approach enables us to map parallel stream processing applications to parallel hardware efficiently. The safety concepts anchored in Rust ensure the reliability of the resulting implementation. We demonstrate our approach's practical applicability with two case studies: the word count problem and aircraft telemetry decoding.","PeriodicalId":202581,"journal":{"name":"2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126807653","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}

引用次数: 3

On-chip Parallel Photonic Reservoir Computing using Multiple Delay Lines 基于多延迟线的片上并行光子库计算

2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) Pub Date : 2020-09-01 DOI: 10.1109/SBAC-PAD49847.2020.00015

S. Hasnain, R. Mahapatra

引用次数: 2

Optimizing Green Energy Consumption of Fog Computing Architectures 优化雾计算架构的绿色能耗

2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) Pub Date : 2020-09-01 DOI: 10.1109/SBAC-PAD49847.2020.00021

A. Gougeon, Benjamin Camus, Anne-Cécile Orgerie

{"title":"Optimizing Green Energy Consumption of Fog Computing Architectures","authors":"A. Gougeon, Benjamin Camus, Anne-Cécile Orgerie","doi":"10.1109/SBAC-PAD49847.2020.00021","DOIUrl":"https://doi.org/10.1109/SBAC-PAD49847.2020.00021","url":null,"abstract":"The Cloud already represents an important part of the global energy consumption, and this consumption keeps increasing. Many solutions have been investigated to increase its energy efficiency and to reduce its environmental impact. However, with the introduction of new requirements, notably in terms of latency, an architecture complementary to the Cloud is emerging: the Fog. The Fog computing paradigm represents a distributed architecture closer to the end-user. Its necessity and feasibility keep being demonstrated in recent works. However, its impact on energy consumption is often neglected and the integration of renewable energy has not been considered yet. The goal of this work is to exhibit an energy-efficient Fog architecture considering the integration of renewable energy. We explore three resource allocation algorithms and three consolidation policies. Our simulation results, based on real traces, show that the intrinsic low computing capability of the nodes in a Fog context makes it harder to exploit renewable energy. In addition, the share of the consumption from the communication network between the computing resources increases in this context, and the communication devices are even harder to power through renewable sources.","PeriodicalId":202581,"journal":{"name":"2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127335772","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}

引用次数: 5

A Fast and Concise Parallel Implementation of the 8x8 2D IDCT using Halide 使用卤化物的8x8 2D IDCT的快速简洁并行实现

2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) Pub Date : 2020-09-01 DOI: 10.1109/SBAC-PAD49847.2020.00032

Martin J. Johnson, D. Playne

引用次数: 0

Online Sharing-Aware Thread Mapping in Software Transactional Memory 软件事务性内存中支持在线共享的线程映射

2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) Pub Date : 2020-09-01 DOI: 10.1109/SBAC-PAD49847.2020.00016

Douglas Pereira Pasqualin, M. Diener, A. R. D. Bois, M. Pilla

{"title":"Online Sharing-Aware Thread Mapping in Software Transactional Memory","authors":"Douglas Pereira Pasqualin, M. Diener, A. R. D. Bois, M. Pilla","doi":"10.1109/SBAC-PAD49847.2020.00016","DOIUrl":"https://doi.org/10.1109/SBAC-PAD49847.2020.00016","url":null,"abstract":"Software Transactional Memory (STM) is an alternative abstraction to synchronize processes in parallel programming. One advantage is simplicity since it is possible to replace the use of explicit locks with atomic blocks. Regarding STM performance, many studies already have been made focusing on reducing the number of aborts. However, in current multicore architectures with complex memory hierarchies, it is also important to consider where the memory of a program is allocated and how it is accessed. This paper proposes the use of a technique called sharing-aware mapping, which maps threads to cores of an application based on their memory access behavior, to achieve better performance in STM systems. We introduce STMap, an online, low overhead mechanism to detect the sharing behavior and perform the mapping directly inside the STM library, by tracking and analyzing how threads perform STM operations. In experiments with the STAMP benchmark suite and synthetic benchmarks, STMap shows performance gains of up to 77% on a Xeon system (17.5% on average) and 85% on an Opteron system (9.1% on average), compared to the Linux scheduler.","PeriodicalId":202581,"journal":{"name":"2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127867442","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}

引用次数: 4