aho_corasick | A C++ implementation of the aho corasick pattern search | Learning library
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kandi X-RAY | aho_corasick Summary
A C++ implementation of the aho corasick pattern search algorithm
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QUESTION
I want to cross compile a Rust program from my x86 Mac to a binary that can run on a Silicon Mac, and I can't figure out linking.
I have:
- An x86 Mac running macOS 10.15.7 Catalina
- A Rust project called
riff cargo 1.51.0 (43b129a20 2021-03-16)recently retrieved using rustup- Xcode version 12.4 (12D4e)
I want to compile this into a binary that can run on a Silicon (ARM) Mac. This could be one of:
- A Silicon specific binary
- A Universal binary that can run on either Silicon or x86
I have tried (through ./release.sh --dry):
rustup target add aarch64-apple-darwincargo build --release --target=aarch64-apple-darwin
The result was too long to paste in here, so this is an excerpt:
...ANSWER
Answered 2021-Mar-30 at 17:34Add the appropriate target
QUESTION
I am new to oneAPI and similar frameworks, so I am having trouble with data management using SYCL data buffers.
My task is to find substrings in a given string using Aho-Corasick algorithm.
My Idea was to build a trie and after that submit a kernel that would parallelly find substrings in the trie. So for that I created a SYCL queue, created buffers for string (the one to find substrings in), for vector (to store the result of the search) and for my Aho-Corasick object, which contains the root of the previously built trie. However, about the last one I'm not sure, since I am creating a buffer for an object in host memory, that contains pointers to other objects (such as Nodes, that contain pointers to other Nodes).
The structure of Node object:
...ANSWER
Answered 2020-May-11 at 12:05if I understood correctly, you are attempting to use std::unordered_map, std::string and std::set in device code. I'm not an expert on Intel-specific oneAPI SYCL extensions, but in pure SYCL 1.2.1 this is not allowed and I would be surprised if this works in DPC++.
The SYCL 1.2.1 spec does not really define how SYCL interacts with the standard library. While some implementations may be able to make some guarantees about certain well-defined portions of the standard library working in devie code as an extension (commonly e.g. std:: math functions), this is not universally guaranteed across SYCL implementations.
Additionally supporting STL containers in device code (which is not required by the SYCL spec) I would imagine to be particularly difficult and I've never heard of a SYCL implementation supporting that. This is because containers typically employ mechanisms unsupported in SYCL device code because they require runtime support, for example throwing exceptions. Because on, say, a GPU there's no C++ runtime, such mechanisms cannot work in SYCL.
It is also important to understand that this is not really a SYCL-specific limitation, but a common restriction among heterogeneous programming models. Other heterogeneous programming models such as CUDA impose similar restrictions for similar reasons.
Another difficulty with containers in kernels is that STL data structures are usually not really designed for the massively parallel SIMT execution model on a SYCL device, making them prone to race conditions.
The final probem is the one you have already identified: You are copying pointers to host memory. Since you are on oneAPI DPC++, the easiest solution to work with pointer-based data structures is to use the Intel SYCL extension of unified shared memory (USM) which can be used to generate pointers that are valid both on host and device. There is also a USM allocator that could be passed to containers if they were supported in device code.
QUESTION
New to CUDA and gpu programming, having trouble with copying array of object pointers to device.
I have a vector of object pointers, each object contains two vectors, that I will be working with in device code.
I need to somehow copy that array into the device memory, however after reading similar solutions, still can't figure it out.
This is the structure of an object, I'm working with:
...ANSWER
Answered 2020-May-09 at 20:33 auto **nodesPtr = (aho_corasick::Node **) malloc(a->nodes.size() * sizeof(aho_corasick::Node *));
int i = 0;
for (auto &node: a->nodes) {
auto *newNode = new aho_corasick::Node(' ');
cudaMalloc((void **) &(newNode->cudaChildren), sizeof(int) * node->children.size());
cudaMemcpy(newNode->cudaChildren, node->children.data(), sizeof(int) * node->children.size(),
cudaMemcpyHostToDevice);
cudaMalloc((void **) &(newNode->cudaRets), sizeof(int) * node->retVals.size());
cudaMemcpy(newNode->cudaRets, node->retVals.data(), sizeof(int) * node->retVals.size(),
cudaMemcpyHostToDevice);
newNode->retsCount = node->retVals.size();
aho_corasick::Node *devNode;
cudaMalloc((void **) &devNode, sizeof(aho_corasick::Node));
cudaMemcpy(devNode, newNode, sizeof(aho_corasick::Node), cudaMemcpyHostToDevice);
nodesPtr[i++] = devNode;
}
aho_corasick::Node **devNodes;
cudaMalloc((void ***) &devNodes, a->nodes.size() * sizeof(aho_corasick::Node *));
cudaMemcpy(devNodes, nodesPtr, a->nodes.size() * sizeof(aho_corasick::Node *), cudaMemcpyHostToDevice);
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