Warning I've stopped maintaining this project !
OpenCL powered Merklization using BLAKE3
Few weeks ago, when I completed writing Binary Merklization Kernel using Rescue Prime Hash function for performing 2-to-1 hashing, I also decided to take a look at much faster BLAKE3 hash; using it for 2-to-1 hashing, constructing all intermediate nodes of Binary Merkle Tree, when N -many leaf nodes are provided, where N = 2 ^ i | i = {1, 2, 3 ...}
And here I'm today.
I've implemented Binary Merklization logic using BLAKE3 as 2-to-1 hash function for computing intermediate node when two of its immediate children are provided. Output of BLAKE3 hash function is 32 -bytes. Meaning, if N -leaf nodes are to be used for constructing Merkle Tree, I've N << 5 -bytes input to work with. Each OpenCL work-item will take 64 -bytes input i.e. two contiguous (leaf/ intermediate) nodes of Merkle Tree on some level concatenated, where each node of Merkle Tree is represented using 32 -bytes ( output of BLAKE3 digest ). Each work-item will compress 64 -bytes input message and produce 32 -bytes output digest, which is an intermediate node. Note, in BLAKE3 input is splitted into chunks ( each of 1024 -bytes width ) and each chunk is splitted into 16 blocks each of 64 -bytes width. That means, here in BLAKE3 2-to-1 hashing case, I'll be working with only one input chunk, which has single block of width 64 -bytes.
2-to-1 BLAKE3 hash function naturally lends itself well to parallelization efforts using OpenCL vector intrinsics. I suggest you read BLAKE3 specification's section 5.3 for understanding how SIMD benefits BLAKE3 implementation here.
If you happen to be interested in my 2-to-1 Rescue Prime hash based Binary Merklization implementation, consider taking a look here.
During this implementation I took my ideas from my previous blake3 implementation in SYCL, which is majorly targeted towards a usecase where you've relatively large input byte array ( say 1GB ) & you want to just compute single 32 -bytes digest, as fast as possible. See that implementation here.
I've always taken help from BLAKE3 reference implementation.
- I'm using GNU/ Linux machine
$ lsb_release -d
Description: Ubuntu 20.04.3 LTS- As compiler I'm using
clang-14
clang --version
clang version 14.0.0 (https://github.com/intel/llvm 04c18f2f5697bb334b4cae288254fafccc1f5b81)
Target: x86_64-unknown-linux-gnu
Thread model: posix
InstalledDir: /home/ubuntu/sycl_workspace/llvm/build/bin- For ease of building source code, I use
makeutility - For formatting source files, I use
clang-formatwith Mozilla code format style - You must have both OpenCL ICD & OpenCl development headers installed. You might want to see.
- To quickly verify list of accessible OpenCL accelerators, consider using
clinfo
sudo apt-get install clinfo- I wanted to check what's supported OpenCL C version on my development machine, so I executed following command on bash
$ clinfo | grep -i 'device opencl c'
Device OpenCL C Version OpenCL C 1.2
Device OpenCL C Version OpenCL C 3.0Two outputs because this machine has two platforms
$ clinfo -l
Platform #0: Intel(R) FPGA Emulation Platform for OpenCL(TM)
`-- Device #0: Intel(R) FPGA Emulation Device
Platform #1: Intel(R) OpenCL
`-- Device #0: Intel(R) Xeon(R) CPU E5-2686 v4 @ 2.30GHzThis is a header-only library, you can pretty easily use it in your project by just adding ./include to your project's INCLUDE_PATH. You'll probably be interested in ./include/merklize.h file, which has host portion of Binary Merklization implementation. Only ./kernel.cl contains device executable code.
I suggest you go through code, for getting a sense of how to use this implementation. I've tried accompanying source with some comments, for helping you with that.
Note, this implementation is only helpful when you've relatively large number of leaf nodes and you want to quickly compute all intermediate nodes of Binary Merkle Tree using BLAKE3 2-to-1 hashing.
Just to enforce aforementioned fact, I've also put one check that # -of leaf nodes of Merkle Tree is at least 2 ^ 20.
For benchmarking OpenCL accelerated Binary Merklization implementation using 2-to-1 BLAKE3 hashing, I set up random input byte array of size {32 MB, 64 MB, ... 1GB}, which are interpreted as contiguous blocks of 32 little endian bytes, making {2 ^ 20, 2 ^ 21, ... 2 ^ 25} -many leaf nodes of Binary Merkle Tree. Now, with multiple kernel dispatch rounds all (N - 1) -many intermediate nodes of Binary Merkle Tree with N -many leaf nodes are computed, which are then interpreted as little endian bytes making cl_uint -> cl_uchar[4].
In following results, I show how much time was spent on executing kernels ( because multiple rounds of them are dispatched ), how much time spent on transferring input bytes to device & also how long does it take to transfer back intermediate node bytes from device to host, all seperately. Their real life execution may overlap, because data dependency graph allows that & I've explicitly enabled OUT_OF_ORDER execution of commands.
Command used for running benchmark
make # build executable, with JIT compiling kernel
./run # executeNote, it's possible to AOT compile kernel to Intermediate Representation language ( read spirv ), using following command
make aot && ./runAs effect of successful execution of above command, 6 new IR files should be created.
$ file kernel_*
kernel_0.bc: LLVM IR bitcode
kernel_0.spv: Khronos SPIR-V binary, little-endian, version 0x00010000, generator 0x0006000e
kernel_1.bc: LLVM IR bitcode
kernel_1.spv: Khronos SPIR-V binary, little-endian, version 0x00010000, generator 0x0006000e
kernel_2.bc: LLVM IR bitcode
kernel_2.spv: Khronos SPIR-V binary, little-endian, version 0x00010000, generator 0x0006000eAmong these 6 files three of them are LLVM bitcodes of compile time preprocessed variants of same kernel.cl, and other 3 are respective spirv 64 -bit IL forms of these LLVM IRs. These spirv64 files are of our interest, as they'll be consumed at runtime for constructing OpenCL program objects, which are then compiled using backend compiler, generating device specific binaries, before computation can be offloaded to accelerators.
This may be useful guide for understanding various tools available for offline compilation of OpenCL kernels.
Remove intermediate object files using
make clean
running on Tesla V100-SXM2-16GB
passed blake3 hash test !
Benchmarking Binary Merklization using BLAKE3
merklized 2 ^ 20 leaves in 3.7582 ms with host to device data tx in 5.9588 ms while device to host data tx took 25.7536 ms
merklized 2 ^ 21 leaves in 7.2841 ms with host to device data tx in 12.4451 ms while device to host data tx took 52.9835 ms
merklized 2 ^ 22 leaves in 14.2924 ms with host to device data tx in 19.1883 ms while device to host data tx took 102.1858 ms
merklized 2 ^ 23 leaves in 28.2952 ms with host to device data tx in 35.7116 ms while device to host data tx took 201.9709 ms
merklized 2 ^ 24 leaves in 52.5327 ms with host to device data tx in 71.5775 ms while device to host data tx took 405.8741 ms
merklized 2 ^ 25 leaves in 100.6062 ms with host to device data tx in 143.8628 ms while device to host data tx took 809.7079 ms# number of available CPU(s)
$ lscpu | grep -i cpu\(s\) | head -1
CPU(s): 128
---------------------------------------------------------------------
running on Intel(R) Xeon(R) Platinum 8358 CPU @ 2.60GHz
passed blake3 hash test !
Benchmarking Binary Merklization using BLAKE3
merklized 2 ^ 20 leaves in 59.3219 ms with host to device data tx in 5.3638 ms while device to host data tx took 3.4559 ms
merklized 2 ^ 21 leaves in 86.8682 ms with host to device data tx in 9.6732 ms while device to host data tx took 6.1324 ms
merklized 2 ^ 22 leaves in 50.9794 ms with host to device data tx in 22.8543 ms while device to host data tx took 5.5853 ms
merklized 2 ^ 23 leaves in 70.0997 ms with host to device data tx in 33.7137 ms while device to host data tx took 10.5920 ms
merklized 2 ^ 24 leaves in 98.0322 ms with host to device data tx in 45.2110 ms while device to host data tx took 20.6102 ms
merklized 2 ^ 25 leaves in 175.9160 ms with host to device data tx in 64.6548 ms while device to host data tx took 40.7421 ms# number of available CPU(s)
$ lscpu | grep -i cpu\(s\) | head -1
CPU(s): 24
---------------------------------------------------------------------
running on Intel(R) Core(TM) i9-10920X CPU @ 3.50GHz
passed blake3 hash test !
Benchmarking Binary Merklization using BLAKE3
merklized 2 ^ 20 leaves in 19.3894 ms with host to device data tx in 3.5966 ms while device to host data tx took 2.7474 ms
merklized 2 ^ 21 leaves in 28.1566 ms with host to device data tx in 6.8970 ms while device to host data tx took 5.5447 ms
merklized 2 ^ 22 leaves in 40.1784 ms with host to device data tx in 14.3582 ms while device to host data tx took 11.0112 ms
merklized 2 ^ 23 leaves in 68.7388 ms with host to device data tx in 25.1962 ms while device to host data tx took 21.8632 ms
merklized 2 ^ 24 leaves in 134.6519 ms with host to device data tx in 46.9249 ms while device to host data tx took 43.4311 ms
merklized 2 ^ 25 leaves in 270.3394 ms with host to device data tx in 87.3723 ms while device to host data tx took 84.2431 ms# number of available CPU(s)
$ lscpu | grep -i cpu\(s\) | head -1
CPU(s): 24
---------------------------------------------------------------------
running on Intel(R) Xeon(R) Gold 6128 CPU @ 3.40GHz
passed blake3 hash test !
Benchmarking Binary Merklization using BLAKE3
merklized 2 ^ 20 leaves in 23.2566 ms with host to device data tx in 4.6335 ms while device to host data tx took 2.3862 ms
merklized 2 ^ 21 leaves in 32.3493 ms with host to device data tx in 8.9893 ms while device to host data tx took 4.0934 ms
merklized 2 ^ 22 leaves in 48.7371 ms with host to device data tx in 16.6954 ms while device to host data tx took 7.9074 ms
merklized 2 ^ 23 leaves in 83.0458 ms with host to device data tx in 27.9030 ms while device to host data tx took 15.5969 ms
merklized 2 ^ 24 leaves in 156.7341 ms with host to device data tx in 44.2649 ms while device to host data tx took 31.1593 ms
merklized 2 ^ 25 leaves in 310.1746 ms with host to device data tx in 75.0253 ms while device to host data tx took 62.2082 ms# number of available CPU(s)
$ lscpu | grep -i cpu\(s\) | head -1
CPU(s): 12
---------------------------------------------------------------------
running on Intel(R) Xeon(R) E-2176G CPU @ 3.70GHz
passed blake3 hash test !
Benchmarking Binary Merklization using BLAKE3
merklized 2 ^ 20 leaves in 13.5114 ms with host to device data tx in 11.7123 ms while device to host data tx took 2.3868 ms
merklized 2 ^ 21 leaves in 26.0523 ms with host to device data tx in 5.3010 ms while device to host data tx took 4.6691 ms
merklized 2 ^ 22 leaves in 50.5436 ms with host to device data tx in 9.8895 ms while device to host data tx took 9.2759 ms
merklized 2 ^ 23 leaves in 98.6148 ms with host to device data tx in 19.0315 ms while device to host data tx took 18.4084 ms
merklized 2 ^ 24 leaves in 196.5320 ms with host to device data tx in 37.5133 ms while device to host data tx took 36.7274 ms
merklized 2 ^ 25 leaves in 393.0303 ms with host to device data tx in 74.4886 ms while device to host data tx took 72.5261 ms# number of available CPU(s)
$ lscpu | grep -i cpu\(s\) | head -1
CPU(s): 4
---------------------------------------------------------------------
running on Intel(R) Xeon(R) CPU E5-2686 v4 @ 2.30GHz
passed blake3 hash test !
Benchmarking Binary Merklization using BLAKE3
merklized 2 ^ 20 leaves in 63.8268 ms with host to device data tx in 9.5565 ms while device to host data tx took 9.7178 ms
merklized 2 ^ 21 leaves in 136.0081 ms with host to device data tx in 18.2696 ms while device to host data tx took 18.3540 ms
merklized 2 ^ 22 leaves in 263.3239 ms with host to device data tx in 36.0957 ms while device to host data tx took 36.8454 ms
merklized 2 ^ 23 leaves in 541.0337 ms with host to device data tx in 73.5482 ms while device to host data tx took 75.0540 ms
merklized 2 ^ 24 leaves in 1092.4356 ms with host to device data tx in 146.4404 ms while device to host data tx took 148.4563 ms
merklized 2 ^ 25 leaves in 2129.8265 ms with host to device data tx in 292.8271 ms while device to host data tx took 305.3257 msrunning on Intel(R) Iris(R) Xe MAX Graphics [0x4905]
passed blake3 hash test !
Benchmarking Binary Merklization using BLAKE3
merklized 2 ^ 20 leaves in 9.1614 ms with host to device data tx in 8.9756 ms while device to host data tx took 5.9159 ms
merklized 2 ^ 21 leaves in 18.1686 ms with host to device data tx in 17.8592 ms while device to host data tx took 11.8276 ms
merklized 2 ^ 22 leaves in 36.1911 ms with host to device data tx in 35.6105 ms while device to host data tx took 23.6581 ms
merklized 2 ^ 23 leaves in 72.2722 ms with host to device data tx in 71.1157 ms while device to host data tx took 47.3124 ms
merklized 2 ^ 24 leaves in 144.4273 ms with host to device data tx in 142.0968 ms while device to host data tx took 94.6267 ms
merklized 2 ^ 25 leaves in 288.7912 ms with host to device data tx in 284.0003 ms while device to host data tx took 189.2569 msrunning on Intel(R) UHD Graphics P630 [0x3e96]
passed blake3 hash test !
Benchmarking Binary Merklization using BLAKE3
merklized 2 ^ 20 leaves in 55.6401 ms with host to device data tx in 4.1337 ms while device to host data tx took 11.5352 ms
merklized 2 ^ 21 leaves in 93.9523 ms with host to device data tx in 8.1561 ms while device to host data tx took 4.5567 ms
merklized 2 ^ 22 leaves in 122.8529 ms with host to device data tx in 16.5308 ms while device to host data tx took 7.9646 ms
merklized 2 ^ 23 leaves in 185.1349 ms with host to device data tx in 32.7902 ms while device to host data tx took 15.7615 ms
merklized 2 ^ 24 leaves in 301.7459 ms with host to device data tx in 63.4848 ms while device to host data tx took 31.5628 ms
merklized 2 ^ 25 leaves in 559.1572 ms with host to device data tx in 111.6804 ms while device to host data tx took 61.9394 ms
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