Efficient direct convolution using long SIMD instructions

This paper demonstrates that state-of-the-art proposals to compute convolutions on architectures with CPUs supporting SIMD instructions deliver poor performance for long SIMD lengths due to frequent cache conflict misses. We first discuss how to adapt the state-of-the-art SIMD direct convolution to architectures using long SIMD instructions and analyze the implications of increasing the SIMD length on the algorithm formulation. Next, we propose two new algorithmic approaches: the Bounded Direct Convolution (BDC), which adapts the amount of computation exposed to mitigate cache misses, and the Multi-Block Direct Convolution (MBDC), which redefines the activation memory layout to improve the memory access pattern. We evaluate BDC, MBDC, the state-of-the-art technique, and a proprietary library on an architecture featuring CPUs with 16,384-bit SIMD registers using ResNet convolutions. Our results show that BDC and MBDC achieve respective speed-ups of 1.44× and 1.28× compared to the state-of-the-art technique for ResNet-101, and 1.83× and 1.63× compared to the proprietary library.This work receives EuroHPC-JU funding under grant no. 101034126, with support from the Horizon2020 program. Adrià Armejach is a Serra Hunter Fellow and has been partially supported by the Grant IJCI-2017-33945 funded by MCIN/AEI/10.13039/501100011033. Marc Casas has been par-tially supported by the Grant RYC-2017-23269 funded by MCIN/AEI/10.13039/501100011033 and ESF Investing in your future. This work is supported by the Spanish Ministry of Science and Technology through the PID2019-107255GB project and the Generalitat de Catalunya (contract 2017-SGR-1414).Peer ReviewedPostprint (author's final draft

レイテンシ耐性を持つベクトルプロセッサアーキテクチャに関する研究

Tohoku University博士（情報科学）thesi

Analytical Query Processing Using Heterogeneous SIMD Instruction Sets

Numerous applications gather increasing amounts of data, which have to be managed and queried. Different hardware developments help to meet this challenge. The grow-ing capacity of main memory enables database systems to keep all their data in memory. Additionally, the hardware landscape is becoming more diverse. A plethora of homo-geneous and heterogeneous co-processors is available, where heterogeneity refers not only to a different computing power, but also to different instruction set architectures. For instance, modern Intel® CPUs offer different instruction sets supporting the Single Instruction Multiple Data (SIMD) paradigm, e.g. SSE, AVX, and AVX512. Database systems have started to exploit SIMD to increase performance. However, this is still a challenging task, because existing algorithms were mainly developed for scalar processing and because there is a huge variety of different instruction sets, which were never standardized and have no unified interface. This requires to completely rewrite the source code for porting a system to another hardware architecture, even if those archi-tectures are not fundamentally different and designed by the same company. Moreover, operations on large registers, which are the core principle of SIMD processing, behave counter-intuitively in several cases. This is especially true for analytical query process-ing, where different memory access patterns and data dependencies caused by the com-pression of data, challenge the limits of the SIMD principle. Finally, there are physical constraints to the use of such instructions affecting the CPU frequency scaling, which is further influenced by the use of multiple cores. This is because the supply power of a CPU is limited, such that not all transistors can be powered at the same time. Hence, there is a complex relationship between performance and power, and therefore also between performance and energy consumption. This thesis addresses the specific challenges, which are introduced by the application of SIMD in general, and the heterogeneity of SIMD ISAs in particular. Hence, the goal of this thesis is to exploit the potential of heterogeneous SIMD ISAs for increasing the performance as well as the energy-efficiency

A Systematic Review and Meta-Analysis of the Incidence of Injury in Professional Female Soccer

The epidemiology of injury in male professional football is well documented and has been used as a basis to monitor injury trends and implement injury prevention strategies. There are no systematic reviews that have investigated injury incidence in women’s professional football. Therefore, the extent of injury burden in women’s professional football remains unknown. PURPOSE: The primary aim of this study was to calculate an overall incidence rate of injury in senior female professional soccer. The secondary aims were to provide an incidence rate for training and match play. METHODS: PubMed, Discover, EBSCO, Embase and ScienceDirect electronic databases were searched from inception to September 2018. Two reviewers independently assessed study quality using the Strengthening the Reporting of Observational Studies in Epidemiology statement using a 22-item STROBE checklist. Seven prospective studies (n=1137 professional players) were combined in a pooled analysis of injury incidence using a mixed effects model. Heterogeneity was evaluated using the Cochrane Q statistic and I2. RESULTS: The epidemiological incidence proportion over one season was 0.62 (95% CI 0.59 - 0.64). Mean total incidence of injury was 3.15 (95% CI 1.54 - 4.75) injuries per 1000 hours. The mean incidence of injury during match play was 10.72 (95% CI 9.11 - 12.33) and during training was 2.21 (95% CI 0.96 - 3.45). Data analysis found a significant level of heterogeneity (total Incidence, X2 = 16.57 P < 0.05; I2 = 63.8%) and during subsequent sub group analyses in those studies reviewed (match incidence, X2 = 76.4 (d.f. = 7), P <0.05; I2 = 90.8%, training incidence, X2 = 16.97 (d.f. = 7), P < 0.05; I2 = 58.8%). Appraisal of the study methodologies revealed inconsistency in the use of injury terminology, data collection procedures and calculation of exposure by researchers. Such inconsistencies likely contribute to the large variance in the incidence and prevalence of injury reported. CONCLUSIONS: The estimated risk of sustaining at least one injury over one football season is 62%. Continued reporting of heterogeneous results in population samples limits meaningful comparison of studies. Standardising the criteria used to attribute injury and activity coupled with more accurate methods of calculating exposure will overcome such limitations