blocks | Enable bcache or LVM on existing block devices

 by   g2p Python Version: Current License: GPL-3.0

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Enable bcache or LVM on existing block devices
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            blocks Examples and Code Snippets

            Blocks
            npmdot img1Lines of Code : 94dot img1no licencesLicense : No License
            copy iconCopy
            // bad
            if (test)
              return false;
            
            // good
            if (test) return false;
            
            // good
            if (test) {
              return false;
            }
            
            // bad
            function foo() { return false; }
            
            // good
            function bar() {
              return false;
            }
            
            
            // bad
            if (test) {
              thing1();
              thing2();
            }
            else {
              thin  
            Splits an argument into blocks .
            pythondot img2Lines of Code : 20dot img2License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def split_arg_into_blocks(block_dims, block_dims_fn, arg, axis=-1):
              """Split `x` into blocks matching `operators`'s `domain_dimension`.
            
              Specifically, if we have a blockwise lower-triangular matrix, with block
              sizes along the diagonal `[M_j, M_  
            Generates blocks of the given bitstring
            pythondot img3Lines of Code : 18dot img3License : Permissive (MIT License)
            copy iconCopy
            def getBlock(bitString):
                """[summary]
                Iterator:
                        Returns by each call a list of length 16 with the 32 bit
                        integer blocks.
            
                Arguments:
                        bitString {[string]} -- [binary string >= 512]
                """
            
                currPo  
            Process child blocks .
            pythondot img4Lines of Code : 15dot img4License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def _process_parallel_blocks(self, parent, children):
                # Because the scopes are not isolated, processing any child block
                # modifies the parent state causing the other child blocks to be
                # processed incorrectly. So we need to checkpoint the  

            Community Discussions

            QUESTION

            Unexpected behaviours with Raku lambdas that are supposed to be equal (I guess)
            Asked 2022-Apr-04 at 18:53

            I'm learning Raku as a passion project and I wanted to implement a simple fizzbuzz, why is join only retaining buzz if I write lambdas with pointy blocks?

            ...

            ANSWER

            Answered 2022-Mar-27 at 22:27

            Because lots of things in Raku are blocks, even things that don't look like it. In particular, this includes the "argument" to control flow like if.

            Source https://stackoverflow.com/questions/71640655

            QUESTION

            AttributeError: Can't get attribute 'new_block' on
            Asked 2022-Feb-25 at 13:18

            I was using pyspark on AWS EMR (4 r5.xlarge as 4 workers, each has one executor and 4 cores), and I got AttributeError: Can't get attribute 'new_block' on . Below is a snippet of the code that threw this error:

            ...

            ANSWER

            Answered 2021-Aug-26 at 14:53

            I had the same error using pandas 1.3.2 in the server while 1.2 in my client. Downgrading pandas to 1.2 solved the problem.

            Source https://stackoverflow.com/questions/68625748

            QUESTION

            How std::atomic wait operation works?
            Asked 2022-Jan-24 at 07:38

            Starting C++20, std::atomic has wait() and notify_one()/notify_all() operations. But I didn't get exactly how they are supposed to work. cppreference says:

            Performs atomic waiting operations. Behaves as if it repeatedly performs the following steps:

            • Compare the value representation of this->load(order) with that of old.
              • If those are equal, then blocks until *this is notified by notify_one() or notify_all(), or the thread is unblocked spuriously.
              • Otherwise, returns.

            These functions are guaranteed to return only if value has changed, even if underlying implementation unblocks spuriously.

            I don't exactly get how these 2 parts are related to each other. Does it mean that if the value if not changed, then the function does not return even if I use notify_one()/notify_all() method? meaning that the operation is somehow equal to following pseudocode?

            ...

            ANSWER

            Answered 2022-Jan-24 at 07:38

            Yes, that is exactly it. notify_one/all simply provide the waiting thread a chance to check the value for change. If it remains the same, e.g. because a different thread has set the value back to its original value, the thread will remain blocking.

            Note: A valid implementation for this code is to use a global array of mutexes and condition_variables. atomic variables are then mapped to these objects by their pointer via a hash function. That's why you get spurious wakeups. Some atomics share the same condition_variable.

            Something like this:

            Source https://stackoverflow.com/questions/70812376

            QUESTION

            Paramiko authentication fails with "Agreed upon 'rsa-sha2-512' pubkey algorithm" (and "unsupported public key algorithm: rsa-sha2-512" in sshd log)
            Asked 2022-Jan-13 at 14:49

            I have a Python 3 application running on CentOS Linux 7.7 executing SSH commands against remote hosts. It works properly but today I encountered an odd error executing a command against a "new" remote server (server based on RHEL 6.10):

            encountered RSA key, expected OPENSSH key

            Executing the same command from the system shell (using the same private key of course) works perfectly fine.

            On the remote server I discovered in /var/log/secure that when SSH connection and commands are issued from the source server with Python (using Paramiko) sshd complains about unsupported public key algorithm:

            userauth_pubkey: unsupported public key algorithm: rsa-sha2-512

            Note that target servers with higher RHEL/CentOS like 7.x don't encounter the issue.

            It seems like Paramiko picks/offers the wrong algorithm when negotiating with the remote server when on the contrary SSH shell performs the negotiation properly in the context of this "old" target server. How to get the Python program to work as expected?

            Python code

            ...

            ANSWER

            Answered 2022-Jan-13 at 14:49

            Imo, it's a bug in Paramiko. It does not handle correctly absence of server-sig-algs extension on the server side.

            Try disabling rsa-sha2-* on Paramiko side altogether:

            Source https://stackoverflow.com/questions/70565357

            QUESTION

            error_code":403,"description":"Forbidden: bot was blocked by the user. error handle in python
            Asked 2022-Jan-10 at 01:46

            I have a problem using telebot API in python. If the user sends a message to the bot and waits for the response and at the same time he blocks the bot. I get this error and the bot will not respond for other users:

            403,"description":"Forbidden: bot was blocked by the user

            Try, catch block is not handling this error for me

            any other idea to get rid of this situation? how to find out that the bot is blocked by the user and avoid replying to this message?

            this is my code:

            ...

            ANSWER

            Answered 2021-Aug-27 at 08:13

            This doesn't appear to actually be an error and thus try catch won't be able to handle it for you. You'll have to get the return code and handle it with if else statements probably (switch statements would work better in this case, but I don't think python has the syntax for it).

            EDIT

            Following the method calls here it looks like reply_to() returns send_message(), which returns a Message object, which contains a json string set to self.json in the __init__() method. In that string you can likely find the status code (400s and 500s you can catch and deal with as you need).

            Source https://stackoverflow.com/questions/68912583

            QUESTION

            Is it possible to combine type constraints in Rust?
            Asked 2021-Dec-16 at 12:44

            I've been working in quite a number of statically-typed programming languages (C++, Haskell, ...), but am relatively new to Rust.

            I often end up writing code like this:

            ...

            ANSWER

            Answered 2021-Dec-16 at 12:19

            You can accomplish this by making your own trait that takes the other traits as a bound, then add a blanket implementation for it:

            Source https://stackoverflow.com/questions/70378140

            QUESTION

            GEMM kernel implemented using AVX2 is faster than AVX2/FMA on a Zen 2 CPU
            Asked 2021-Dec-14 at 20:40

            I have tried speeding up a toy GEMM implementation. I deal with blocks of 32x32 doubles for which I need an optimized MM kernel. I have access to AVX2 and FMA.

            I have two codes (in ASM, I apologies for the crudeness of the formatting) defined below, one is making use of AVX2 features, the other uses FMA.

            Without going into micro benchmarks, I would like to try to develop an understanding (theoretical) of why the AVX2 implementation is 1.11x faster than the FMA version. And possibly how to improve both versions.

            The codes below are for a 3000x3000 MM of doubles and the kernels are implemented using the classical, naive MM with an interchanged deepest loop. I'm using a Ryzen 3700x/Zen 2 as development CPU.

            I have not tried unrolling aggressively, in fear that the CPU might run out of physical registers.

            AVX2 32x32 MM kernel:

            ...

            ANSWER

            Answered 2021-Dec-13 at 21:36

            Zen2 has 3 cycle latency for vaddpd, 5 cycle latency for vfma...pd. (https://uops.info/).

            Your code with 8 accumulators has enough ILP that you'd expect close to two FMA per clock, about 8 per 5 clocks (if there aren't other bottlenecks) which is a bit less than the 10/5 theoretical max.

            vaddpd and vmulpd actually run on different ports on Zen2 (unlike Intel), port FP2/3 and FP0/1 respectively, so it can in theory sustain 2/clock vaddpd and vmulpd. Since the latency of the loop-carried dependency is shorter, 8 accumulators are enough to hide the vaddpd latency if scheduling doesn't let one dep chain get behind. (But at least multiplies aren't stealing cycles from it.)

            Zen2's front-end is 5 instructions wide (or 6 uops if there are any multi-uop instructions), and it can decode memory-source instructions as a single uop. So it might well be doing 2/clock each multiply and add with the non-FMA version.

            If you can unroll by 10 or 12, that might hide enough FMA latency and make it equal to the non-FMA version, but with less power consumption and more SMT-friendly to code running on the other logical core. (10 = 5 x 2 would be just barely enough, which means any scheduling imperfections lose progress on a dep chain which is on the critical path. See Why does mulss take only 3 cycles on Haswell, different from Agner's instruction tables? (Unrolling FP loops with multiple accumulators) for some testing on Intel.)

            (By comparison, Intel Skylake runs vaddpd/vmulpd on the same ports with the same latency as vfma...pd, all with 4c latency, 0.5c throughput.)

            I didn't look at your code super carefully, but 10 YMM vectors might be a tradeoff between touching two pairs of cache lines vs. touching 5 total lines, which might be worse if a spatial prefetcher tries to complete an aligned pair. Or might be fine. 12 YMM vectors would be three pairs, which should be fine.

            Depending on matrix size, out-of-order exec may be able to overlap inner loop dep chains between separate iterations of the outer loop, especially if the loop exit condition can execute sooner and resolve the mispredict (if there is one) while FP work is still in flight. That's an advantage to having fewer total uops for the same work, favouring FMA.

            Source https://stackoverflow.com/questions/70340734

            QUESTION

            C++ algorithm to sum contiguous blocks of integers
            Asked 2021-Nov-03 at 23:40

            Given a block size N and a vector of integers of length k * N which can be viewed as k blocks of N integers, I want to create a new vector of length k whose elements are the sums of the blocks of the original vector.

            E.g. block size 2, vector {1,2,3,4,5,6} would give a result of {3,7,11}.

            E.g. block size 3, vector {0,0,0,1,1,1} would give a result of {0,3}.

            A simple approach that works:

            ...

            ANSWER

            Answered 2021-Oct-31 at 16:28

            If you can use the range-v3 library, you could write the function like this:

            Source https://stackoverflow.com/questions/69788364

            QUESTION

            How to preserve trailing spaces in java 15 text blocks
            Asked 2021-Nov-03 at 16:07

            When defining a String using text blocks by default the trailing white space gets removed as it's treated as incidental white space.

            ...

            ANSWER

            Answered 2021-Nov-03 at 14:10

            This can be done using an escape sequence for space at the end of a line. E.g.

            Source https://stackoverflow.com/questions/69826367

            QUESTION

            C++17 PMR:: Set number of blocks and their size in a unsynchronized_pool_resource
            Asked 2021-Oct-29 at 14:52

            Is any rule for setting in the most effective way the number of blocks in a chunk (max_blocks_per_chunk) and the largest required block (largest_required_pool_block), in a unsynchronized_pool_resource?

            How to avoid unnecessary memory allocations?

            For example have a look in this demo.

            How to reduce the number of allocation that take place as much as possible?

            ...

            ANSWER

            Answered 2021-Oct-29 at 14:52

            Pooled allocators function on a memory waste vs upstream allocator calls trade-off. Reducing one will almost always increase the other and vice-versa.

            On top of that, one of the primary reason behind their use (in my experience, at least) is to limit or outright eliminate memory fragmentation for long-running processes in memory-constrained scenarios. So it is sort of assumed that "throwing more memory at the problem" is going to be counterproductive more often than not.

            Because of this, there is no universal one-size-fit-all rule here. What is preferable will invariably be dictated by the needs of your application.

            Figuring out the correct values for max_blocks_per_chunk and largest_required_pool_block is ideally based on a thorough memory usage analysis so that the achieved balance benefits the application as much as possible.

            However, given the wording of the question:

            How to avoid unnecessary memory allocations?

            How to reduce the number of allocation that take place as much as possible?

            If you want to minimize upstream allocator calls as much as possible, then it's simple:

            • Make largest_required_pool_block the largest frequent allocation size you expect the allocator to face. Larger blocks means more allocations will qualify for pooled allocation.
            • Make max_blocks_per_chunk as large as you dare, up to the maximum number of concurrent allocations for any given block size. More blocks per chunks means more allocations between requests to the upstream.

            The only limiting factor is how much memory footprint bloat you are willing to tolerate for your application.

            Source https://stackoverflow.com/questions/69629967

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