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Last active December 28, 2015 03:39
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GPU Matrix Transpose Notebook
{
"metadata": {
"language": "Julia",
"name": ""
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"GPU Memory Bandwidth Transpose Examples"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"using PyPlot"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import OpenCL\n",
"const cl = OpenCL;"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"BLOCK_SIZE = 16;"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"naive_transpose = \"\n",
"__kernel void transpose(__global *a_t,\n",
" __global *a,\n",
" unsigned a_width,\n",
" unsigned a_height)\n",
"{\n",
" int read_idx = get_global_id(0) + get_global_id(1) * a_width;\n",
" int write_idx = get_global_id(1) + get_global_id(0) * a_height;\n",
" a_t[write_idx] = a[read_idx];\n",
"}\";"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"block_transpose = \"\n",
"#define BLOCK_SIZE $(BLOCK_SIZE)\n",
"__kernel __attribute__((reqd_work_group_size(BLOCK_SIZE, BLOCK_SIZE, 1)))\n",
"void transpose(__global float *a_t, \n",
" __global float *a,\n",
" unsigned a_width,\n",
" unsigned a_height,\n",
" __local float *a_local)\n",
"{\n",
" int base_idx_a = get_group_id(0) * BLOCK_SIZE + get_group_id(1) * (BLOCK_SIZE * a_width);\n",
" int base_idx_a_t = get_group_id(1) * BLOCK_SIZE + get_group_id(0) * (BLOCK_SIZE * a_height);\n",
"\n",
" int glob_idx_a = base_idx_a + get_local_id(0) + a_width * get_local_id(1);\n",
" int glob_idx_a_t = base_idx_a_t + get_local_id(0) + a_height * get_local_id(1);\n",
"\n",
" a_local[get_local_id(1) * BLOCK_SIZE + get_local_id(0)] = a[glob_idx_a];\n",
"\n",
" barrier(CLK_LOCAL_MEM_FENCE);\n",
"\n",
" a_t[glob_idx_a_t] = a_local[get_local_id(0) * BLOCK_SIZE + get_local_id(1)];\n",
"}\";"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"function enqueue_naive_kernel{T}(queue::cl.CmdQueue,\n",
" k::cl.Kernel,\n",
" dst::cl.Buffer{T},\n",
" src::cl.Buffer{T},\n",
" dims)\n",
" h, w = dims\n",
" @assert w % BLOCK_SIZE == 0\n",
" @assert h % BLOCK_SIZE == 0\n",
" cl.set_args!(k, dst, src, uint32(h), uint32(h))\n",
" cl.enqueue_kernel(queue, k, (h, w), (BLOCK_SIZE, BLOCK_SIZE))\n",
"end"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 2,
"text": [
"enqueue_naive_kernel (generic function with 1 method)"
]
}
],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"function enqueue_block_kernel{T}(queue::cl.CmdQueue,\n",
" k::cl.Kernel,\n",
" dst::cl.Buffer{T},\n",
" src::cl.Buffer{T},\n",
" dims::Dims)\n",
" h, w = dims\n",
" @assert w % BLOCK_SIZE == 0\n",
" @assert h % BLOCK_SIZE == 0\n",
" lmem = cl.LocalMem(Float32, BLOCK_SIZE * (BLOCK_SIZE + 1))\n",
" cl.set_args!(k, dst, src, uint32(h), uint32(w), lmem)\n",
" cl.enqueue_kernel(queue, k, (h, w), (BLOCK_SIZE, BLOCK_SIZE))\n",
"end "
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 3,
"text": [
"enqueue_block_kernel (generic function with 1 method)"
]
}
],
"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"function benchmark_transpose()\n",
"\n",
" gpu_device = first(cl.devices(:gpu))\n",
" ctx = cl.Context(gpu_device)\n",
" \n",
" for dev in cl.devices(ctx)\n",
" @assert dev[:local_mem_size] > 0\n",
" end\n",
" \n",
" prg = cl.Program(ctx, source=naive_transpose) |> cl.build!\n",
" naive_kern = cl.Kernel(prg, \"transpose\")\n",
" \n",
" prg = cl.Program(ctx, source=block_transpose) |> cl.build!\n",
" block_kernel = cl.Kernel(prg, \"transpose\")\n",
" \n",
" queue = cl.CmdQueue(ctx, :profile) \n",
" \n",
" array_sizes = [int((2^i) / 32) * 32 for i in 6:12]\n",
"\n",
" mem_bandwiths = Float32[]\n",
" for (name, method, kern) in ((\"naive\", enqueue_naive_kernel, naive_kern), \n",
" (\"block\", enqueue_block_kernel, block_kernel))\n",
" for s in array_sizes \n",
" src = rand(Float32, (s, s))\n",
" a_buf = cl.Buffer(Float32, ctx, (:r, :copy), hostbuf=src)\n",
" a_t_buf = cl.Buffer(Float32, ctx, :w, sizeof(src))\n",
" \n",
" # warm up....\n",
" for i in 1:4\n",
" method(queue, kern, a_t_buf, a_buf, size(src))\n",
" end\n",
" \n",
" # profile...\n",
" count = 20\n",
" events = cl.Event[]\n",
" for i in 1:count\n",
" push!(events, method(queue, kern, a_t_buf, a_buf, size(src)))\n",
" end\n",
" cl.wait(events[end])\n",
" \n",
" time = sum([evt[:profile_duration] for evt in events])\n",
" mem_bw = 2 * sizeof(src) * count / (time * 1e-9)\n",
" push!(mem_bandwiths, mem_bw)\n",
" \n",
" @printf(\"benchmarking %s, array size: %s^2, %.3f GB/s\\n\", name, s, mem_bw / 1e9)\n",
" \n",
" # causes problems with ijulia's show...\n",
" #cl.release!(a_buf)\n",
" #cl.release!(a_t_buf)\n",
" end\n",
" end\n",
" \n",
" # plot results, sleep a little to prevent overlap with show..\n",
" sleep(1)\n",
" clf()\n",
" n_sizes = length(array_sizes)\n",
" naive_bandwidths = mem_bandwiths[1:n_sizes]\n",
" block_bandwidths = mem_bandwiths[n_sizes+1:end]\n",
" plot(array_sizes, naive_bandwidths/1e9, \"o-\", label=\"naive\")\n",
" plot(array_sizes, block_bandwidths/1e9, \"o-\", label=\"block\")\n",
" title(\"Tanspose Tests for $(gpu_device[:name])\")\n",
" xlabel(\"Matrix width/height N\")\n",
" ylabel(\"Memory Bandwidth [GB/s]\")\n",
" legend(loc=\"best\")\n",
" grid(true)\n",
" show()\n",
"end"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 4,
"text": [
"benchmark_transpose (generic function with 1 method)"
]
}
],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"benchmark_transpose()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"benchmarking naive"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
", array size: 64^2, 1.601 GB/s\n",
"benchmarking naive, array size: 128^2, 14.433 GB/s\n",
"benchmarking naive, array size: 256^2, 21.358 GB/s\n",
"benchmarking naive, array size: 512^2, 13.429 GB/s\n",
"benchmarking naive, array size: 1024^2, 10.693 GB/s\n",
"benchmarking "
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"naive, array size: 2048^2, 17.667 GB/s\n",
"benchmarking "
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"naive, array size: 4096^2, 7.202 GB/s\n",
"benchmarking block, array size: 64^2, 10.869 GB/s\n",
"benchmarking block, array size: 128^2, 42.130 GB/s\n",
"benchmarking block, array size: 256^2, 113.791 GB/s\n",
"benchmarking block, array size: 512^2, 100.789 GB/s\n",
"benchmarking block, array size: 1024^2, 52.034 GB/s\n",
"benchmarking "
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"block, array size: 2048^2, 20.124 GB/s\n",
"benchmarking "
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"block, array size: 4096^2, 8.435 GB/s\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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