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Ashton @misyltoad","VK_VALVE_video_encode_rgb_conversion",{"title":1867,"description":1868,"body":1869,"_type":3981,"_id":1867},"VK_ARM_tensors.proposal","This document describes a proposal for a new type of resource to represent\nthe high-dimensionality structured and formatted data used in machine learning\napplications.",{"type":1870,"children":1871,"toc":3962},"root",[1872,1879,1886,1891,1896,1911,1916,1922,1929,1943,1948,1953,1959,1995,2000,2006,2011,2034,2039,2045,2050,2144,2150,2171,2243,2248,2392,2420,2456,2461,2482,2488,2495,2506,2524,2530,2547,2553,2564,2570,2575,2635,2641,2647,2652,3485,3491,3496,3617,3623,3934,3940,3945,3951,3956],{"type":1873,"tag":1874,"props":1875,"children":1876},"element","p",{},[1877],{"type":1878,"value":1868},"text",{"type":1873,"tag":1880,"props":1881,"children":1883},"h2",{"id":1882},"_problem_statement",[1884],{"type":1878,"value":1885},"Problem Statement",{"type":1873,"tag":1874,"props":1887,"children":1888},{},[1889],{"type":1878,"value":1890},"Vulkan is used more and more for machine learning applications and in particular\nneural network inference. In these applications, data is typically organized in\n4- or 5-dimensional arrays of numbers called tensors. There is no construct in\nVulkan today to directly represent structured and formatted data with that high\na dimensionality.",{"type":1873,"tag":1874,"props":1892,"children":1893},{},[1894],{"type":1878,"value":1895},"This makes interoperability with machine learning accelerators not exposed via\nVulkan more difficult to implement efficiently and portably for applications\nand does not allow implementers to make the best out of their hardware.\nApplications today have to use buffers and images which each come with their\nshortcomings:",{"type":1873,"tag":1897,"props":1898,"children":1899},"ul",{},[1900,1906],{"type":1873,"tag":1901,"props":1902,"children":1903},"li",{},[1904],{"type":1878,"value":1905},"Buffers are mostly unstructured and unformatted (texel buffers are of little\nhelp in machine learning use cases). They require applications to hardcode the\nexact layout of data in memory in compiled shaders accessing tensors which\nmakes it very difficult for implementations to retrofit structure and use\ndedicated data handling hardware. Consequently, buffers also prevent the use\nof implementation-specific data layout optimizations in portable programs.",{"type":1873,"tag":1901,"props":1907,"children":1908},{},[1909],{"type":1878,"value":1910},"Images do have some of the attributes necessary to represent tensor data\nand expose data handling hardware (structuredness, formatting, layout\nabstraction, out-of-bounds behavior, etc) but, in their current form, do not\ngenerically support more than 3 dimensions.",{"type":1873,"tag":1874,"props":1912,"children":1913},{},[1914],{"type":1878,"value":1915},"Looking toward the future of machine learning on Vulkan, it is clear the\nrapid emergence of neural graphics use cases will require a much tighter\nintegration of machine learning accelerators (that commonly operate on whole\ntensors) into Vulkan as well as an increase in the capabilities of GPU hardware\nto efficiently handle tensors. This makes a software construct to adequately\nrepresent tensors a key building block to any proposal seeking to add\nbuilt-in support for machine learning to Vulkan.",{"type":1873,"tag":1880,"props":1917,"children":1919},{"id":1918},"_solution_space",[1920],{"type":1878,"value":1921},"Solution Space",{"type":1873,"tag":1923,"props":1924,"children":1926},"h3",{"id":1925},"_structured_buffers",[1927],{"type":1878,"value":1928},"Structured buffers",{"type":1873,"tag":1874,"props":1930,"children":1931},{},[1932,1934,1941],{"type":1878,"value":1933},"One solution is to layer structure on top of buffers. For example, a\n'Buffer structured view' that would be associated to a new ",{"type":1873,"tag":1935,"props":1936,"children":1938},"code",{"className":1937},[],[1939],{"type":1878,"value":1940},"VkDescriptorType",{"type":1878,"value":1942},"\ncould be introduced to declare the dimensionality and formatting of the data\nas well as its layout in memory. A matching set of shader-side accessors to\nload/store data using a coordinate system for addressing could be used.",{"type":1873,"tag":1874,"props":1944,"children":1945},{},[1946],{"type":1878,"value":1947},"While the core of such a solution looks simple and could cater for basic needs,\na closer inspection reveals the need for a lot of surrounding functionality to\nreport supported dimensionalities, data formats, etc. Furthermore, the\nintroduction of a new descriptor type requires, on the shader side, either a\nmatching type of object, or at the very least decorations, or accepting that\nthose structured buffers could also be accessed in an unstructured way in the\nsame shaders, defeating the original goal.",{"type":1873,"tag":1874,"props":1949,"children":1950},{},[1951],{"type":1878,"value":1952},"By the time all those problems have been resolved, a possible solution has\nlittle in common with buffers, negating the benefits (cost savings, simplicity,\netc) of reusing buffers.",{"type":1873,"tag":1923,"props":1954,"children":1956},{"id":1955},"_extended_images",[1957],{"type":1878,"value":1958},"Extended images",{"type":1873,"tag":1874,"props":1960,"children":1961},{},[1962,1964,1970,1972,1978,1980,1986,1988,1993],{"type":1878,"value":1963},"Images already provide a resource for structured and formatted data and could\npotentially be extended to support higher dimensionalities and target dedicated\ntensor hardware. One could imagine introducing support for 4D/5D images or allowing\narrays of 3D images to cater for the 4D case. This would require bypassing\nexisting data structures that are limited to 3 dimensions\n(e.g. ",{"type":1873,"tag":1935,"props":1965,"children":1967},{"className":1966},[],[1968],{"type":1878,"value":1969},"VkExtend3D",{"type":1878,"value":1971},", ",{"type":1873,"tag":1935,"props":1973,"children":1975},{"className":1974},[],[1976],{"type":1878,"value":1977},"VkOffset3D",{"type":1878,"value":1979},") and introducing new ones to supersede them in\na fairly large number of places. Another difficulty, for implementers that\nhave dedicated tensor handling hardware would be to direct the processing of\nthose images to the right hardware units with a clear distinction between\ntexturing, image load/store and tensor hardware. Usage flags could likely help\nconstruct a solution on the API side but SPIR-V changes look more problematic.\nRelying on a potential extension of the ",{"type":1873,"tag":1981,"props":1982,"children":1983},"em",{},[1984],{"type":1878,"value":1985},"Dim",{"type":1878,"value":1987}," operand to ",{"type":1873,"tag":1981,"props":1989,"children":1990},{},[1991],{"type":1878,"value":1992},"OpTypeImage",{"type":1878,"value":1994}," could\nwork in some cases but would be ambiguous in others (e.g. how to direct 3D\n'tensor images' to dedicated hardware rather than image hardware?).",{"type":1873,"tag":1874,"props":1996,"children":1997},{},[1998],{"type":1878,"value":1999},"Overall, images are already very complex (for good reasons!), come with a lot of\nbaggage, assumptions and many special rules that makes extending them to cater\nto a new set of features, usage patterns and hardware very difficult, inelegant\nand error prone for users.",{"type":1873,"tag":1923,"props":2001,"children":2003},{"id":2002},"_new_tensor_resource_type",[2004],{"type":1878,"value":2005},"New tensor resource type",{"type":1873,"tag":1874,"props":2007,"children":2008},{},[2009],{"type":1878,"value":2010},"Introduce a new tensor resource type to describe N-dimensional structured and\nformatted data as well as shader-side accessors. This new resource type can be\ncrafted to precisely satisfy the needs of both machine learning applications\nand implementers and provide the following additional benefits:",{"type":1873,"tag":1897,"props":2012,"children":2013},{},[2014,2019,2024,2029],{"type":1873,"tag":1901,"props":2015,"children":2016},{},[2017],{"type":1878,"value":2018},"Signal a clear desire for Vulkan to treat tensors and machine learning in\ngeneral as a built-in feature.",{"type":1873,"tag":1901,"props":2020,"children":2021},{},[2022],{"type":1878,"value":2023},"Dedicated object types and accessors make it easier for implementations to\nreason about data dependencies which facilitates the introduction of\nfurther tensor processing functionality.",{"type":1873,"tag":1901,"props":2025,"children":2026},{},[2027],{"type":1878,"value":2028},"A new resource type gives the Vulkan ecosystem a \"clean slate\" to develop\ntensor functionality.",{"type":1873,"tag":1901,"props":2030,"children":2031},{},[2032],{"type":1878,"value":2033},"A new resource type makes it easy to provide support for structured data\ncompression schemes.",{"type":1873,"tag":1874,"props":2035,"children":2036},{},[2037],{"type":1878,"value":2038},"In light of the difficulties with extending buffers and images, and because of\nthe additional benefits it provides, this third option is retained as the\nproposed solution.",{"type":1873,"tag":1880,"props":2040,"children":2042},{"id":2041},"_proposal",[2043],{"type":1878,"value":2044},"Proposal",{"type":1873,"tag":1874,"props":2046,"children":2047},{},[2048],{"type":1878,"value":2049},"A new type of tensor resource is added alongside buffers and images, designed to\nsupport N-dimensional structured and formatted data. Genericity and extensibility\nwere key design goals for this proposal. Here are a few design decisions worth\nhighlighting:",{"type":1873,"tag":1897,"props":2051,"children":2052},{},[2053,2058,2063,2074,2079,2123],{"type":1873,"tag":1901,"props":2054,"children":2055},{},[2056],{"type":1878,"value":2057},"The layout of tensor data can be left to the implementation or controlled by\nthe application to facilitate interoperability with external entities.",{"type":1873,"tag":1901,"props":2059,"children":2060},{},[2061],{"type":1878,"value":2062},"This proposal does not introduce any operations to copy tensor data to/from\nimages and buffers. Memory aliasing is the sole mechanism available to\nexchange data with other resource types. 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