{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T16:13:59Z","timestamp":1782317639332,"version":"3.54.5"},"reference-count":38,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["2045714, 2039070, 2028733, 1763256"],"award-info":[{"award-number":["2045714, 2039070, 2028733, 1763256"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000185","name":"Defense Advanced Research Projects Agency","doi-asserted-by":"publisher","award":["HR001120C0107"],"award-info":[{"award-number":["HR001120C0107"]}],"id":[{"id":"10.13039\/100000185","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Graph."],"published-print":{"date-parts":[[2022,7]]},"abstract":"<jats:p>In this paper we explore the viability of path tracing massive scenes using a \"supercomputer\" constructed on-the-fly from thousands of small, serverless cloud computing nodes. We present R2E2 (Really Elastic Ray Engine) a scene decomposition-based parallel renderer that rapidly acquires thousands of cloud CPU cores, loads scene geometry from a pre-built scene BVH into the aggregate memory of these nodes in parallel, and performs full path traced global illumination using an inter-node messaging service designed for communicating ray data. To balance ray tracing work across many nodes, R2E2 adopts a service-oriented design that statically replicates geometry and texture data from frequently traversed scene regions onto multiple nodes based on estimates of load, and dynamically assigns ray tracing work to lightly loaded nodes holding the required data. We port pbrt's ray-scene intersection components to the R2E2 architecture, and demonstrate that scenes with up to a terabyte of geometry and texture data (where as little as 1\/250th of the scene can fit on any one node) can be path traced at 4K resolution, in tens of seconds using thousands of tiny serverless nodes on the AWS Lambda platform.<\/jats:p>","DOI":"10.1145\/3528223.3530171","type":"journal-article","created":{"date-parts":[[2022,7,22]],"date-time":"2022-07-22T21:06:27Z","timestamp":1658523987000},"page":"1-12","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["R2E2"],"prefix":"10.1145","volume":"41","author":[{"given":"Sadjad","family":"Fouladi","sequence":"first","affiliation":[{"name":"Microsoft Research and Stanford University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brennan","family":"Shacklett","sequence":"additional","affiliation":[{"name":"Stanford University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fait","family":"Poms","sequence":"additional","affiliation":[{"name":"Stanford University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arjun","family":"Arora","sequence":"additional","affiliation":[{"name":"Stanford University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alex","family":"Ozdemir","sequence":"additional","affiliation":[{"name":"Stanford University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deepti","family":"Raghavan","sequence":"additional","affiliation":[{"name":"Stanford University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pat","family":"Hanrahan","sequence":"additional","affiliation":[{"name":"Stanford University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kayvon","family":"Fatahalian","sequence":"additional","affiliation":[{"name":"Stanford University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Keith","family":"Winstein","sequence":"additional","affiliation":[{"name":"Stanford University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,7,22]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/1921479.1921497"},{"key":"e_1_2_2_2_1","unstructured":"Amazon Web Services. 2021. Simple Queue Service (SQS). https:\/\/aws.amazon.com\/sqs\/."},{"key":"e_1_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3267809.3267815"},{"key":"e_1_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3231578.3231581"},{"key":"e_1_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-8659.2009.01378.x"},{"key":"e_1_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3182159"},{"key":"e_1_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-8659.2008.01253.x"},{"key":"e_1_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357223.3362711"},{"key":"e_1_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1111\/1467-8659.t01-1-00702"},{"key":"e_1_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-8659.1986.tb00263.x"},{"key":"e_1_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/964965.808592"},{"key":"e_1_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1111\/cgf.12158"},{"key":"e_1_2_2_13_1","volume-title":"Distributed Caching with Memcached. Linux J","author":"Fitzpatrick Brad","year":"2004","unstructured":"Brad Fitzpatrick. 2004. Distributed Caching with Memcached. Linux J. 2004, 124 (Aug. 2004), 5."},{"key":"e_1_2_2_14_1","volume-title":"2019 USENIX Annual Technical Conference (USENIX ATC 19)","author":"Fouladi Sadjad","year":"2019","unstructured":"Sadjad Fouladi, Francisco Romero, Dan Iter, Qian Li, Shuvo Chatterjee, Christos Kozyrakis, Matei Zaharia, and Keith Winstein. 2019. From laptop to lambda: Outsourcing everyday jobs to thousands of transient functional containers. In 2019 USENIX Annual Technical Conference (USENIX ATC 19). 475--488."},{"key":"e_1_2_2_15_1","volume-title":"14th USENIX Symposium on Networked Systems Design and Implementation (NSDI 17)","author":"Fouladi Sadjad","year":"2017","unstructured":"Sadjad Fouladi, Riad S Wahby, Brennan Shacklett, Karthikeyan Vasuki Balasubramaniam, William Zeng, Rahul Bhalerao, Anirudh Sivaraman, George Porter, and Keith Winstein. 2017. Encoding, fast and slow: Low-latency video processing using thousands of tiny threads. In 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI 17). 363--376."},{"key":"e_1_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3182160"},{"key":"e_1_2_2_17_1","volume-title":"4th Eurographics Workshop on Rendering. 27 -- 46","author":"Jansen F.W","year":"1993","unstructured":"F.W Jansen and A.G Chalmers. 1993. Realism in real time?. In 4th Eurographics Workshop on Rendering. 27 -- 46."},{"key":"e_1_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3127479.3128601"},{"key":"e_1_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.2312\/EGPGV\/EGPGV02\/007-016"},{"key":"e_1_2_2_20_1","volume-title":"Load balancing strategies for a parallel ray-tracing system based on constant subdivision. The Visual Computer 4 (07","author":"Kobayashi Hiroaki","year":"1988","unstructured":"Hiroaki Kobayashi, Satoshi Nishimura, Hideyuki Kubota, Tadao Nakamura, and Yoshiharu Shigei. 1988. Load balancing strategies for a parallel ray-tracing system based on constant subdivision. The Visual Computer 4 (07 1988), 197--209."},{"key":"e_1_2_2_21_1","doi-asserted-by":"publisher","unstructured":"J. Mahovsky and B. Wyvill. 2006. Memory-Conserving Bounding Volume Hierarchies with Coherent Raytracing. Computer Graphics Forum (2006). 10.1111\/j.1467-8659.2006.00933.x","DOI":"10.1111\/j.1467-8659.2006.00933.x"},{"key":"e_1_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2013.261"},{"key":"e_1_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.5555\/16564.16573"},{"key":"e_1_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/1778765.1778774"},{"key":"e_1_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/1778765.1778803"},{"key":"e_1_2_2_26_1","unstructured":"Matt Pharr Wenzel Jakob and Greg Humphreys. 2016. Physically based rendering: From theory to implementation. Morgan Kaufmann."},{"key":"e_1_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/258734.258791"},{"key":"e_1_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF01901486"},{"key":"e_1_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/328712.319333"},{"key":"e_1_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/63047.63073"},{"key":"e_1_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF01887591"},{"key":"e_1_2_2_32_1","volume-title":"numpywren: Serverless linear algebra. arXiv preprint arXiv:1810.09679","author":"Shankar Vaishaal","year":"2018","unstructured":"Vaishaal Shankar, Karl Krauth, Qifan Pu, Eric Jonas, Shivaram Venkataraman, Ion Stoica, Benjamin Recht, and Jonathan Ragan-Kelley. 2018. numpywren: Serverless linear algebra. arXiv preprint arXiv:1810.09679 (2018)."},{"key":"e_1_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3105762.3105784"},{"key":"e_1_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/2601097.2601199"},{"key":"e_1_2_2_35_1","unstructured":"Walt Disney Animation Studios. 2018. Moana Island Scene (v1.1). https:\/\/www.disneyanimation.com\/resources\/moana-island-scene\/."},{"key":"e_1_2_2_36_1","volume-title":"Boxer: Data Analytics on Network-enabled Serverless Platforms. In 11th Annual Conference on Innovative Data Systems Research (CIDR'21)","author":"Wawrzoniak Mike","year":"2021","unstructured":"Mike Wawrzoniak, Ingo M\u00fcller, Rodrigo Fraga Barcelos Paulus Bruno, and Gustavo Alonso. 2021. Boxer: Data Analytics on Network-enabled Serverless Platforms. In 11th Annual Conference on Innovative Data Systems Research (CIDR'21)."},{"key":"e_1_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3105762.3105773"},{"key":"e_1_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3105762.3105773"}],"container-title":["ACM Transactions on Graphics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3528223.3530171","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3528223.3530171","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3528223.3530171","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:02:49Z","timestamp":1750186969000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3528223.3530171"}},"subtitle":["low-latency path tracing of terabyte-scale scenes using thousands of cloud CPUs"],"short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":38,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2022,7]]}},"alternative-id":["10.1145\/3528223.3530171"],"URL":"https:\/\/doi.org\/10.1145\/3528223.3530171","relation":{},"ISSN":["0730-0301","1557-7368"],"issn-type":[{"value":"0730-0301","type":"print"},{"value":"1557-7368","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7]]},"assertion":[{"value":"2022-07-22","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}