{"id":168349,"date":"2015-05-19T00:00:00","date_gmt":"2015-05-19T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/kahawai-high-quality-mobile-gaming-using-gpu-offload\/"},"modified":"2018-10-16T22:27:39","modified_gmt":"2018-10-17T05:27:39","slug":"kahawai-high-quality-mobile-gaming-using-gpu-offload","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/kahawai-high-quality-mobile-gaming-using-gpu-offload\/","title":{"rendered":"Kahawai: High-Quality Mobile Gaming Using GPU Offload"},"content":{"rendered":"
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This paper presents Kahawai1<\/sup>, a system that provides high-quality gaming on mobile devices, such as tablets and smartphones, by offloading a portion of the GPU computation to server-side infrastructure. In contrast with previous thin-client approaches that require a server-side GPU to render the entire content, Kahawai uses collaborative rendering to combine the output of a mobile GPU and a server-side GPU into the displayed output. Compared to a thin client, collaborative rendering requires significantly less network bandwidth between the mobile device and the server to achieve the same visual quality and, unlike a thin client, collaborative rendering supports disconnected operation, allowing a user to play offline – albeit with reduced visual quality.<\/p>\n

Kahawai implements two separate techniques for collaborative rendering: (1) a mobile device can render each frame with reduced detail while a server sends a stream of per-frame differences to transform each frame into a high detail version, or (2) a mobile device can render a subset of the frames while a server provides the missing frames. Both techniques are compatible with the hardware-accelerated H.264 video decoders found on most modern mobile devices. We implemented a Kahawai prototype and integrated it with the idTech 4 open-source game engine, an advanced engine used by many commercial games. In our evaluation, we show that Kahawai can deliver gameplay at an acceptable frame rate, and achieve high visual quality using as little as one-sixth of the bandwidth of the conventional thin-client approach. Furthermore, a 50-person user study with our prototype shows that Kahawai can deliver the same gaming experience as a thin client under excellent network conditions.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

This paper presents Kahawai1, a system that provides high-quality gaming on mobile devices, such as tablets and smartphones, by offloading a portion of the GPU computation to server-side infrastructure. In contrast with previous thin-client approaches that require a server-side GPU to render the entire content, Kahawai uses collaborative rendering to combine the output of a […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13551,13547],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-168349","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-graphics-and-multimedia","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"ACM \u2013 Association for Computing Machinery","msr_edition":"","msr_affiliation":"","msr_published_date":"2015-05-19","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"204337","msr_publicationurl":"","msr_doi":"10.1145\/2742647.2742657","msr_publication_uploader":[{"type":"file","title":"mobi093f-cuervoA.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/mobi093f-cuervoA.pdf","id":204337,"label_id":0},{"type":"doi","title":"10.1145\/2742647.2742657","viewUrl":false,"id":false,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":204337,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/mobi093f-cuervoA.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"Eduardo Cuervo","user_id":31486,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Eduardo Cuervo"},{"type":"user_nicename","value":"Alec Wolman","user_id":30925,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Alec Wolman"},{"type":"text","value":"Landon P. 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