I’m trying to do a 2D and 3D compatible spatial hash very similar to the one found here: https://github.com/taichi-dev/taichi/blob/master/examples/pbf2d.py
The way I define the backGrid space is different from that implementation because I couldn’t figure out how to make theirs viable for 3D due to the lack of ti.L (afaik). I also tried to make my backGrid a sparse grid but I was not able to fit the many many snodes needed for this. I basically need a nGrid x nGrid x nGrid x 1024 structure, but for some reason the way I’m doing this causes some seg faulting that makes no sense to me 
I’ve recreated the bug with the code below, it would be amazing if someone could help me figure out what the problem is!
import taichi as ti
import numpy as np
import triangle as tr
#ti.init(default_fp=ti.f64, arch=ti.gpu) # Try to run on GPU #GPU, parallel
ti.init(default_fp=ti.f64, arch=ti.cpu, cpu_max_num_threads=1) #CPU, sequential
#Sparse Grids
#---Params
dim = 3
dx = 0.003
rp = (3*(dx**2))**0.5
invDx = 1.0 / 0.003
nGrid = ti.ceil(invDx)
grid_size = 4096
grid_block_size = 128
leaf_block_size = 16 if dim == 2 else 8
indices = ti.ij if dim == 2 else ti.ijk
offset = tuple(0 for _ in range(dim))
#---Grid Shapes for PID
grid = ti.root.pointer(indices, grid_size // grid_block_size) # 32
block = grid.pointer(indices, grid_block_size // leaf_block_size) # 8
pid = ti.field(int)
block.dynamic(ti.indices(dim), 1024 * 1024, chunk_size=leaf_block_size**dim * 8).place(pid, offset=offset + (0, ))
#---Grid Shapes for Rest of Grid Structures
grid2 = ti.root.pointer(indices, grid_size // grid_block_size) # 32
block2 = grid2.pointer(indices, grid_block_size // leaf_block_size) # 8
def block_component(c):
block2.dense(indices, leaf_block_size).place(c, offset=offset) # 16 in 3D, 8 in 2D (-2048, 2048) or (0, 4096) w/o offset
#Grid Structures
gridNumParticles = ti.field(dtype=int) #track number of particles in each cell using cell index
maxPPC = 2**10
block_component(gridNumParticles) #keep track of how many particles are at each cell of backGrid
backGrid = ti.field(int) #background grid to map grid cells to a list of particles they contain
backGridIndeces = ti.ijk if dim == 2 else ti.ijkl
backGridShape = (nGrid, nGrid, maxPPC) if dim == 2 else (nGrid, nGrid, nGrid, maxPPC)
ti.root.dense(backGridIndeces, backGridShape).place(backGrid) #backGrid is nGrid x nGrid x maxPPC
#Particle Structures
x = ti.Vector.field(dim, dtype=float) # position
mp = ti.field(dtype=float) # particle masses
particle = ti.root.dynamic(ti.i, 2**27, 2**19) #2**20 causes problems in CUDA (maybe asking for too much space)
particle.place(x, mp)
#Neighbor Search Routines
@ti.func
def backGridIdx(x):
#compute int vector of backGrid indeces (recall the grid here )
return int(x/rp)
@ti.func
def stencil_range():
return ti.ndrange(*((3, ) * dim))
def addParticles():
N = 10
w = 0.2
dw = w / N
for i in range(N):
for j in range(N):
for k in range(N):
x[i*(N**2) + j*N + k] = [0.4 + (i * dw), 0.4 + (j * dw), 0.4 + (k * dw)]
mp[i*(N**2) + j*N + k] = 0.001
@ti.kernel
def build_pid():
ti.block_dim(64) #this sets the number of threads per block / block dimension
for p in x:
base = int(ti.floor(x[p] * invDx - 0.5))
ti.append(pid.parent(), base - ti.Vector(list(offset)), p)
@ti.kernel
def backGridSort():
#Sort particles into backGrid
ti.block_dim(256)
ti.no_activate(particle)
for I in ti.grouped(pid):
p = pid[I]
cell = backGridIdx(x[p]) #grab cell idx (vector of ints)
offs = ti.atomic_add(gridNumParticles[cell], 1) #atomically add one to our grid cell's particle count NOTE: returns the OLD value before add
print("cell:", cell, "offs:", offs)
print("backGrid shape:", backGrid.shape)
backGrid[cell, offs] = p #place particle idx into the grid cell bucket at the correct place in the cell's neighbor list (using offs)
addParticles()
grid.deactivate_all()
build_pid()
backGridSort()
The output of this is also below, note the index that’s throwing the error and also the shape of backGrid I’m printing. I don’t see why this index would throw a seg fault here!
[Taichi] mode=release
[Taichi] preparing sandbox at /tmp/taichi-86oajjkm
[Taichi] version 0.6.37, llvm 10.0.0, commit e0ac1d86, linux, python 3.6.9
[Taichi] Starting on arch=x64
[Taichi] materializing...
cell: [76, 76, 76] offs: 0
backGrid shape: [334, 334, 334, 1024]
[E 01/08/21 20:34:28.869] Received signal 11 (Segmentation fault)
***********************************
* Taichi Compiler Stack Traceback *
***********************************
/home/josh/.local/lib/python3.6/site-packages/taichi/core/../lib/taichi_core.so: taichi::Logger::error(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, bool)
/home/josh/.local/lib/python3.6/site-packages/taichi/core/../lib/taichi_core.so: taichi::signal_handler(int)
/lib/x86_64-linux-gnu/libc.so.6(+0x3efd0) [0x7fd521d29fd0]
[0x7fd522198f36]
Internal Error occurred, check this page for possible solutions:
https://taichi.readthedocs.io/en/stable/install.html#troubleshooting