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luau/bench/tests/shootout/scimark.lua
Vyacheslav Egorov aafea36235
Fixed the backwards compatible benchmark support library require ()
Previous benchmark require fix wasn't actually working correctly for the
old style require (or running in Lua).
2023-12-04 12:48:31 -08:00

443 lines
12 KiB
Lua

------------------------------------------------------------------------------
-- Lua SciMark (2010-12-20).
--
-- A literal translation of SciMark 2.0a, written in Java and C.
-- Credits go to the original authors Roldan Pozo and Bruce Miller.
-- See: http://math.nist.gov/scimark2/
------------------------------------------------------------------------------
-- Copyright (C) 2006-2010 Mike Pall. All rights reserved.
--
-- Permission is hereby granted, free of charge, to any person obtaining
-- a copy of this software and associated documentation files (the
-- "Software"), to deal in the Software without restriction, including
-- without limitation the rights to use, copy, modify, merge, publish,
-- distribute, sublicense, and/or sell copies of the Software, and to
-- permit persons to whom the Software is furnished to do so, subject to
-- the following conditions:
--
-- The above copyright notice and this permission notice shall be
-- included in all copies or substantial portions of the Software.
--
-- THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
-- EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
-- MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
-- IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
-- CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
-- TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
-- SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
--
-- [ MIT license: http://www.opensource.org/licenses/mit-license.php ]
------------------------------------------------------------------------------
------------------------------------------------------------------------------
-- Modification to be compatible with Lua 5.3
------------------------------------------------------------------------------
local function prequire(name) local success, result = pcall(require, name); return if success then result else nil end
local bench = script and require(script.Parent.bench_support) or prequire("bench_support") or require("../../bench_support")
function test()
if table and table.unpack then
unpack = table.unpack
end
------------------------------------------------------------------------------
local SCIMARK_VERSION = "2010-12-10"
local SCIMARK_COPYRIGHT = "Copyright (C) 2006-2010 Mike Pall"
local MIN_TIME = 0.2
local RANDOM_SEED = 101009 -- Must be odd.
local SIZE_SELECT = "small"
local benchmarks = {
"FFT", "SOR", "MC", "SPARSE", "LU",
small = {
FFT = { 1024 },
SOR = { 100 },
MC = { },
SPARSE = { 1000, 5000 },
LU = { 100 },
},
large = {
FFT = { 1048576 },
SOR = { 1000 },
MC = { },
SPARSE = { 100000, 1000000 },
LU = { 1000 },
},
}
local abs, log, sin, floor = math.abs, math.log, math.sin, math.floor
local pi, clock = math.pi, os.clock
local format = string.format
------------------------------------------------------------------------------
-- Select array type: Lua tables or native (FFI) arrays
------------------------------------------------------------------------------
local darray, iarray
local function array_init()
if jit and jit.status and jit.status() then
local ok, ffi = pcall(require, "ffi")
if ok then
darray = ffi.typeof("double[?]")
iarray = ffi.typeof("int[?]")
return
end
end
function darray(n) return {} end
iarray = darray
end
------------------------------------------------------------------------------
-- This is a Lagged Fibonacci Pseudo-random Number Generator with
-- j, k, M = 5, 17, 31. Pretty weak, but same as C/Java SciMark.
------------------------------------------------------------------------------
local rand, rand_init
if jit and jit.status and jit.status() then
-- LJ2 has bit operations and zero-based arrays (internally).
local bit = require("bit")
local band, sar = bit.band, bit.arshift
function rand_init(seed)
local Rm, Rj, Ri = iarray(17), 16, 11
for i=0,16 do Rm[i] = 0 end
for i=16,0,-1 do
seed = band(seed*9069, 0x7fffffff)
Rm[i] = seed
end
function rand()
local i = band(Ri+1, sar(Ri-16, 31))
local j = band(Rj+1, sar(Rj-16, 31))
Ri, Rj = i, j
local k = band(Rm[i] - Rm[j], 0x7fffffff)
Rm[j] = k
return k * (1.0/2147483647.0)
end
end
else
-- Better for standard Lua with one-based arrays and without bit operations.
function rand_init(seed)
local Rm, Rj = {}, 1
for i=1,17 do Rm[i] = 0 end
for i=17,1,-1 do
seed = (seed*9069) % (2^31)
Rm[i] = seed
end
function rand()
local j, m = Rj, Rm
local h = j - 5
if h < 1 then h = h + 17 end
local k = m[h] - m[j]
if k < 0 then k = k + 2147483647 end
m[j] = k
if j < 17 then Rj = j + 1 else Rj = 1 end
return k * (1.0/2147483647.0)
end
end
end
local function random_vector(n)
local v = darray(n+1)
for x=1,n do v[x] = rand() end
return v
end
local function random_matrix(m, n)
local a = {}
for y=1,m do
local v = darray(n+1)
a[y] = v
for x=1,n do v[x] = rand() end
end
return a
end
------------------------------------------------------------------------------
-- FFT: Fast Fourier Transform.
------------------------------------------------------------------------------
local function fft_bitreverse(v, n)
local j = 0
for i=0,2*n-4,2 do
if i < j then
v[i+1], v[i+2], v[j+1], v[j+2] = v[j+1], v[j+2], v[i+1], v[i+2]
end
local k = n
while k <= j do j = j - k; k = k / 2 end
j = j + k
end
end
local function fft_transform(v, n, dir)
if n <= 1 then return end
fft_bitreverse(v, n)
local dual = 1
repeat
local dual2 = 2*dual
for i=1,2*n-1,2*dual2 do
local j = i+dual2
local ir, ii = v[i], v[i+1]
local jr, ji = v[j], v[j+1]
v[j], v[j+1] = ir - jr, ii - ji
v[i], v[i+1] = ir + jr, ii + ji
end
local theta = dir * pi / dual
local s, s2 = sin(theta), 2.0 * sin(theta * 0.5)^2
local wr, wi = 1.0, 0.0
for a=3,dual2-1,2 do
wr, wi = wr - s*wi - s2*wr, wi + s*wr - s2*wi
for i=a,a+2*(n-dual2),2*dual2 do
local j = i+dual2
local jr, ji = v[j], v[j+1]
local dr, di = wr*jr - wi*ji, wr*ji + wi*jr
local ir, ii = v[i], v[i+1]
v[j], v[j+1] = ir - dr, ii - di
v[i], v[i+1] = ir + dr, ii + di
end
end
dual = dual2
until dual >= n
end
function benchmarks.FFT(n)
local l2n = log(n)/log(2)
if l2n % 1 ~= 0 then
io.stderr:write("Error: FFT data length is not a power of 2\n")
os.exit(1)
end
local v = random_vector(n*2)
return function(cycles)
local norm = 1.0 / n
for p=1,cycles do
fft_transform(v, n, -1)
fft_transform(v, n, 1)
for i=1,n*2 do v[i] = v[i] * norm end
end
return ((5*n-2)*l2n + 2*(n+1)) * cycles
end
end
------------------------------------------------------------------------------
-- SOR: Jacobi Successive Over-Relaxation.
------------------------------------------------------------------------------
local function sor_run(mat, m, n, cycles, omega)
local om4, om1 = omega*0.25, 1.0-omega
m = m - 1
n = n - 1
for i=1,cycles do
for y=2,m do
local v, vp, vn = mat[y], mat[y-1], mat[y+1]
for x=2,n do
v[x] = om4*((vp[x]+vn[x])+(v[x-1]+v[x+1])) + om1*v[x]
end
end
end
end
function benchmarks.SOR(n)
local mat = random_matrix(n, n)
return function(cycles)
sor_run(mat, n, n, cycles, 1.25)
return (n-1)*(n-1)*cycles*6
end
end
------------------------------------------------------------------------------
-- MC: Monte Carlo Integration.
------------------------------------------------------------------------------
local function mc_integrate(cycles)
local under_curve = 0
local rand = rand
for i=1,cycles do
local x = rand()
local y = rand()
if x*x + y*y <= 1.0 then under_curve = under_curve + 1 end
end
return (under_curve/cycles) * 4
end
function benchmarks.MC()
return function(cycles)
local res = mc_integrate(cycles)
assert(math.sqrt(cycles)*math.abs(res-math.pi) < 5.0, "bad MC result")
return cycles * 4 -- Way off, but same as SciMark in C/Java.
end
end
------------------------------------------------------------------------------
-- Sparse Matrix Multiplication.
------------------------------------------------------------------------------
local function sparse_mult(n, cycles, vy, val, row, col, vx)
for p=1,cycles do
for r=1,n do
local sum = 0
for i=row[r],row[r+1]-1 do sum = sum + vx[col[i]] * val[i] end
vy[r] = sum
end
end
end
function benchmarks.SPARSE(n, nz)
local nr = floor(nz/n)
local anz = nr*n
local vx = random_vector(n)
local val = random_vector(anz)
local vy, col, row = darray(n+1), iarray(nz+1), iarray(n+2)
row[1] = 1
for r=1,n do
local step = floor(r/nr)
if step < 1 then step = 1 end
local rr = row[r]
row[r+1] = rr+nr
for i=0,nr-1 do col[rr+i] = 1+i*step end
end
return function(cycles)
sparse_mult(n, cycles, vy, val, row, col, vx)
return anz*cycles*2
end
end
------------------------------------------------------------------------------
-- LU: Dense Matrix Factorization.
------------------------------------------------------------------------------
local function lu_factor(a, pivot, m, n)
local min_m_n = m < n and m or n
for j=1,min_m_n do
local jp, t = j, abs(a[j][j])
for i=j+1,m do
local ab = abs(a[i][j])
if ab > t then
jp = i
t = ab
end
end
pivot[j] = jp
if a[jp][j] == 0 then error("zero pivot") end
if jp ~= j then a[j], a[jp] = a[jp], a[j] end
if j < m then
local recp = 1.0 / a[j][j]
for k=j+1,m do
local v = a[k]
v[j] = v[j] * recp
end
end
if j < min_m_n then
for i=j+1,m do
local vi, vj = a[i], a[j]
local eij = vi[j]
for k=j+1,n do vi[k] = vi[k] - eij * vj[k] end
end
end
end
end
local function matrix_alloc(m, n)
local a = {}
for y=1,m do a[y] = darray(n+1) end
return a
end
local function matrix_copy(dst, src, m, n)
for y=1,m do
local vd, vs = dst[y], src[y]
for x=1,n do vd[x] = vs[x] end
end
end
function benchmarks.LU(n)
local mat = random_matrix(n, n)
local tmp = matrix_alloc(n, n)
local pivot = iarray(n+1)
return function(cycles)
for i=1,cycles do
matrix_copy(tmp, mat, n, n)
lu_factor(tmp, pivot, n, n)
end
return 2.0/3.0*n*n*n*cycles
end
end
------------------------------------------------------------------------------
-- Main program.
------------------------------------------------------------------------------
local function printf(...)
print(format(...))
end
local function fmtparams(p1, p2)
if p2 then return format("[%d, %d]", p1, p2)
elseif p1 then return format("[%d]", p1) end
return ""
end
local function measure(min_time, name, ...)
array_init()
rand_init(RANDOM_SEED)
local run = benchmarks[name](...)
--[[local cycles = 1
repeat
local tm = clock()
local flops = run(cycles, ...)
tm = clock() - tm
if tm >= min_time then
local res = flops / tm * 1.0e-6
local p1, p2 = ...
printf("%-7s %8.2f %s\n", name, res, fmtparams(...))
return res
end
cycles = cycles * 2
until false]]
run(10, ...)
return 10
end
printf("Lua SciMark %s based on SciMark 2.0a. %s.\n\n",
SCIMARK_VERSION, SCIMARK_COPYRIGHT)
while arg and arg[1] do
local a = table.remove(arg, 1)
if a == "-noffi" then
package.preload.ffi = nil
elseif a == "-small" then
SIZE_SELECT = "small"
elseif a == "-large" then
SIZE_SELECT = "large"
elseif benchmarks[a] then
local p = benchmarks[SIZE_SELECT][a]
measure(MIN_TIME, a, tonumber(arg[1]) or p[1], tonumber(arg[2]) or p[2])
return
else
printf("Usage: scimark [-noffi] [-small|-large] [BENCH params...]\n\n")
printf("BENCH -small -large\n")
printf("---------------------------------------\n")
for _,name in ipairs(benchmarks) do
printf("%-7s %-13s %s\n", name,
fmtparams(unpack(benchmarks.small[name])),
fmtparams(unpack(benchmarks.large[name])))
end
printf("\n")
os.exit(1)
end
end
local params = benchmarks[SIZE_SELECT]
local sum = 0
for _,name in ipairs(benchmarks) do
sum = sum + measure(MIN_TIME, name, unpack(params[name]))
end
--printf("\nSciMark %8.2f [%s problem sizes]\n", sum / #benchmarks, SIZE_SELECT)
end
bench.runCode(test, "scimark")