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906a00d498
* General - Fix the benchmark require wrapper function to work in Lua - Fix memory leak in the new Luau C API test * New Solver - Luau: type functions should be able to signal whether or not irreducibility is due to an error - Do not generate extra expansion constraint for uninvoked user-defined type functions - Print in a user-defined type function should be reported as an error instead of logging to stdout - Many e-graphs bugfixes and performance improvements - Many general bugfixes and improvements to the new solver as a whole - Fixed issue with Luau used-defined type functions not having all environments initialized - Infer types of globals under new type solver * Fragment Autocomplete - Miscellaneous fixes to make interop with the old solver better * Runtime - Support disabling specific Luau built-in functions from being fast-called or constant-evaluated - Added constant folding for vector arithmetic - Added constant propagation and type inference for Vector3 globals ---------------------------------------------------------- 9 contributors: Co-authored-by: Aaron Weiss <aaronweiss@roblox.com> Co-authored-by: Andy Friesen <afriesen@roblox.com> Co-authored-by: Aviral Goel <agoel@roblox.com> Co-authored-by: Daniel Angel <danielangel@roblox.com> Co-authored-by: Jonathan Kelaty <jkelaty@roblox.com> Co-authored-by: Hunter Goldstein <hgoldstein@roblox.com> Co-authored-by: Varun Saini <vsaini@roblox.com> Co-authored-by: Vighnesh Vijay <vvijay@roblox.com> Co-authored-by: Vyacheslav Egorov <vegorov@roblox.com>
40 lines
1 KiB
Lua
40 lines
1 KiB
Lua
local function prequire(name) local success, result = pcall(require, name); return success and result end
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local bench = script and require(script.Parent.bench_support) or prequire("bench_support") or require("../bench_support")
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local function mmul(matrix1, matrix2)
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local shapeRows = #matrix1
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local shapeColumns = #matrix2[1]
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local result = table.create(shapeRows)
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for i = 1, shapeRows do
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result[i] = table.create(shapeColumns)
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for j = 1, shapeColumns do
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local sum = 0
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for k = 1, shapeColumns do
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sum = sum + matrix1[i][k] * matrix2[k][j]
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end
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result[i][j] = sum
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end
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end
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return result
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end
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function test()
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local n = 100
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local mat = table.create(n)
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for i = 1, n do
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local t = table.create(n)
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for k = 1, n do
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t[k] = math.random()
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end
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mat[i] = t
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end
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local startTime = os.clock()
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local result = mmul(mat, mat)
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return os.clock() - startTime
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end
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bench.runCode(test, "matrixmult")
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