Mary W. Hall, P. Kogge, J. Koller, P. Diniz, Jacqueline Chame, J. Draper, J. LaCoss, J. Granacki, J. Brockman, Apoorv Srivastava, W. Athas, V. Freeh, Jaewook Shin, Joonseok Park
{"title":"将不规则应用程序映射到DIVA,一种基于pim的数据密集型体系结构","authors":"Mary W. Hall, P. Kogge, J. Koller, P. Diniz, Jacqueline Chame, J. Draper, J. LaCoss, J. Granacki, J. Brockman, Apoorv Srivastava, W. Athas, V. Freeh, Jaewook Shin, Joonseok Park","doi":"10.1145/331532.331589","DOIUrl":null,"url":null,"abstract":"Processing-in-memory (PIM) chips that integrate processor logic into memory devices offer a new opportunity for bridging the growing gap between processor and memory speeds, especially for applications with high memory-bandwidth requirements. The Data-IntensiVe Architecture (DIVA) system combines PIM memories with one or more external host processors and a PIM-to-PIM interconnect. DIVA increases memory bandwidth through two mechanisms: (1) performing selected computation in memory, reducing the quantity of data transferred across the processor-memory interface; and (2) providing communication mechanisms called parcels for moving both data and computation throughout memory, further bypassing the processor-memory bus. DIVA uniquely supports acceleration of important irregular applications, including sparse-matrix and pointer-based computations. In this paper, we focus on several aspects of DIVA designed to effectively support such computations at very high performance levels: (1) the memory model and parcel definitions; (2) the PIM-to-PIM interconnect; and, (3) requirements for the processor-to-memory interface. We demonstrate the potential of PIM-based architectures in accelerating the performance of three irregular computations, sparse conjugate gradient, a natural-join database operation and an object-oriented database query.","PeriodicalId":354898,"journal":{"name":"ACM/IEEE SC 1999 Conference (SC'99)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"226","resultStr":"{\"title\":\"Mapping Irregular Applications to DIVA, a PIM-based Data-Intensive Architecture\",\"authors\":\"Mary W. Hall, P. Kogge, J. Koller, P. Diniz, Jacqueline Chame, J. Draper, J. LaCoss, J. Granacki, J. Brockman, Apoorv Srivastava, W. Athas, V. Freeh, Jaewook Shin, Joonseok Park\",\"doi\":\"10.1145/331532.331589\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Processing-in-memory (PIM) chips that integrate processor logic into memory devices offer a new opportunity for bridging the growing gap between processor and memory speeds, especially for applications with high memory-bandwidth requirements. The Data-IntensiVe Architecture (DIVA) system combines PIM memories with one or more external host processors and a PIM-to-PIM interconnect. DIVA increases memory bandwidth through two mechanisms: (1) performing selected computation in memory, reducing the quantity of data transferred across the processor-memory interface; and (2) providing communication mechanisms called parcels for moving both data and computation throughout memory, further bypassing the processor-memory bus. DIVA uniquely supports acceleration of important irregular applications, including sparse-matrix and pointer-based computations. In this paper, we focus on several aspects of DIVA designed to effectively support such computations at very high performance levels: (1) the memory model and parcel definitions; (2) the PIM-to-PIM interconnect; and, (3) requirements for the processor-to-memory interface. We demonstrate the potential of PIM-based architectures in accelerating the performance of three irregular computations, sparse conjugate gradient, a natural-join database operation and an object-oriented database query.\",\"PeriodicalId\":354898,\"journal\":{\"name\":\"ACM/IEEE SC 1999 Conference (SC'99)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"226\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM/IEEE SC 1999 Conference (SC'99)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/331532.331589\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM/IEEE SC 1999 Conference (SC'99)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/331532.331589","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mapping Irregular Applications to DIVA, a PIM-based Data-Intensive Architecture
Processing-in-memory (PIM) chips that integrate processor logic into memory devices offer a new opportunity for bridging the growing gap between processor and memory speeds, especially for applications with high memory-bandwidth requirements. The Data-IntensiVe Architecture (DIVA) system combines PIM memories with one or more external host processors and a PIM-to-PIM interconnect. DIVA increases memory bandwidth through two mechanisms: (1) performing selected computation in memory, reducing the quantity of data transferred across the processor-memory interface; and (2) providing communication mechanisms called parcels for moving both data and computation throughout memory, further bypassing the processor-memory bus. DIVA uniquely supports acceleration of important irregular applications, including sparse-matrix and pointer-based computations. In this paper, we focus on several aspects of DIVA designed to effectively support such computations at very high performance levels: (1) the memory model and parcel definitions; (2) the PIM-to-PIM interconnect; and, (3) requirements for the processor-to-memory interface. We demonstrate the potential of PIM-based architectures in accelerating the performance of three irregular computations, sparse conjugate gradient, a natural-join database operation and an object-oriented database query.