luau/bench/tests/shootout/scimark.lua
Vyacheslav Egorov aafea36235
Fixed the backwards compatible benchmark support library require (#1125)
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

444 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")