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DLL scatter manual mapper
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QUESTION
I have a list of all CpG locations (base pair value) for a gene on a methylation array in one table (table a), and another table with the locations (base pair value) for 12 CpGs for the same gene not present on the array (table b). I am trying to work out for each probe in table_b, which probe in table_a is the closest in bp.
i.e. table_a
...ANSWER
Answered 2022-Apr-14 at 11:26Joining is equivalent to filtering the cross-product. We can sort all combinations of rows from both tables to pick the one with the closest distance:
QUESTION
I'm working on a procfs kernel extension for macOS and trying to implement a feature that emulates Linux’s /proc/cpuinfo similar to what FreeBSD does with its linprocfs. Since I'm trying to learn, and since not every bit of FreeBSD code can simply be copied over to XNU and be expected to work right out of the jar, I'm writing this feature from scratch, with FreeBSD and NetBSD's linux-based procfs features as a reference. Anyways...
Under Linux, $cat /proc/cpuinfo showes me something like this:
...ANSWER
Answered 2022-Mar-18 at 07:54There is no need to allocate memory for this task: pass a pointer to a local array along with its size and use strlcat
properly:
QUESTION
Using the os/exec
package, I want to run an external command on a *nix OS with another user instead of root. (The main process runs under root user).
The external command runs by go app. But my app can not read /proc/pid/smaps
file, following error:
ANSWER
Answered 2022-Mar-05 at 17:54I test my code inside a docker container that doesn't have SYS_PTRACE
capability. That's why the error shows. The error was gone when I added the SYS_PTRACE
capability for that container.
QUESTION
#include
#include
#include
#include
#include
using namespace std;
static inline void stick_this_thread_to_core(int core_id);
static inline void* incrementLoop(void* arg);
struct BenchmarkData {
long long iteration_count;
int core_id;
};
pthread_barrier_t g_barrier;
int main(int argc, char** argv)
{
if(argc != 3) {
cout << "Usage: ./a.out " << endl;
return EXIT_FAILURE;
}
cout << "================================================ STARTING ================================================" << endl;
int core1 = std::stoi(argv[1]);
int core2 = std::stoi(argv[2]);
pthread_barrier_init(&g_barrier, nullptr, 2);
const long long iteration_count = 100'000'000'000;
BenchmarkData benchmark_data1{iteration_count, core1};
BenchmarkData benchmark_data2{iteration_count, core2};
pthread_t worker1, worker2;
pthread_create(&worker1, nullptr, incrementLoop, static_cast(&benchmark_data1));
cout << "Created worker1" << endl;
pthread_create(&worker2, nullptr, incrementLoop, static_cast(&benchmark_data2));
cout << "Created worker2" << endl;
pthread_join(worker1, nullptr);
cout << "Joined worker1" << endl;
pthread_join(worker2, nullptr);
cout << "Joined worker2" << endl;
return EXIT_SUCCESS;
}
static inline void stick_this_thread_to_core(int core_id) {
int num_cores = sysconf(_SC_NPROCESSORS_ONLN);
if (core_id < 0 || core_id >= num_cores) {
cerr << "Core " << core_id << " is out of assignable range.\n";
return;
}
cpu_set_t cpuset;
CPU_ZERO(&cpuset);
CPU_SET(core_id, &cpuset);
pthread_t current_thread = pthread_self();
int res = pthread_setaffinity_np(current_thread, sizeof(cpu_set_t), &cpuset);
if(res == 0) {
cout << "Thread bound to core " << core_id << " successfully." << endl;
} else {
cerr << "Error in binding this thread to core " << core_id << '\n';
}
}
static inline void* incrementLoop(void* arg)
{
BenchmarkData* arg_ = static_cast(arg);
int core_id = arg_->core_id;
long long iteration_count = arg_->iteration_count;
stick_this_thread_to_core(core_id);
cout << "Thread bound to core " << core_id << " will now wait for the barrier." << endl;
pthread_barrier_wait(&g_barrier);
cout << "Thread bound to core " << core_id << " is done waiting for the barrier." << endl;
long long data = 0;
long long i;
cout << "Thread bound to core " << core_id << " will now increment private data " << iteration_count / 1'000'000'000.0 << " billion times." << endl;
std::chrono::steady_clock::time_point begin = std::chrono::steady_clock::now();
for(i = 0; i < iteration_count; ++i) {
++data;
__asm__ volatile("": : :"memory");
}
std::chrono::steady_clock::time_point end = std::chrono::steady_clock::now();
unsigned long long elapsed_time = std::chrono::duration_cast(end - begin).count();
cout << "Elapsed time: " << elapsed_time << " ms, core: " << core_id << ", iteration_count: " << iteration_count << ", data value: " << data << ", i: " << i << endl;
return nullptr;
}
...ANSWER
Answered 2022-Jan-13 at 08:40It turns out that cores 0, 16, 17 were running at much higher frequency on my Skylake server.
QUESTION
I wrote a small program to explore out-of-bounds reads vulnerabilities in C to better understand them; this program is intentionally buggy and has vulnerabilities:
...ANSWER
Answered 2021-Dec-31 at 23:21Since stdout
is line buffered, putchar
doesn't write to the terminal directly; it puts the character into a buffer, which is flushed when a newline is encountered. And the buffer for stdout
happens to be located on the heap following your heap_book
allocation.
So at some point in your copy, you putchar
all the characters of your secretinfo
method. They are now in the output buffer. A little later, heap_book[i]
is within the stdout
buffer itself, so you encounter the copy of secretinfo
that is there. When you putchar
it, you effectively create another copy a little further along in the buffer, and the process repeats.
You can verify this in your debugger. The address of the stdout buffer, on glibc, can be found with p stdout->_IO_buf_base
. In my test it's exactly 160 bytes past heap_book
.
QUESTION
I've started working with Puppeteer and for some reason I cannot get it to work on my box. This error seems to be a common problem (SO1, SO2) but all of the solutions do not solve this error for me. I have tested it with a clean node package (see reproduction) and I have taken the example from the official Puppeteer 'Getting started' webpage.
How can I resolve this error?
Versions and hardware ...ANSWER
Answered 2021-Nov-24 at 18:42There's too much for me to put this in a comment, so I will summarize here. Maybe it will help you, or someone else. I should also mention this is for RHEL EC2 instances behind a corporate proxy (not Arch Linux), but I still feel like it may help. I had to do the following to get puppeteer working. This is straight from my docs, but I had to hand-jam the contents because my docs are on an intranet.
I had to install all of these libraries manually. I also don't know what the Arch Linux equivalents are. Some are duplicates from your question, but I don't think they all are:
pango
libXcomposite
libXcursor
libXdamage
libXext
libXi
libXtst
cups-libs
libXScrnSaver
libXrandr
GConf2
alsa-lib
atk
gtk3
ipa-gothic-fonts
xorg-x11-fonts-100dpi
xorg-x11-fonts-75dpi
xorg-x11-utils
xorg-x11-fonts-cyrillic
xorg-x11-fonts-Type1
xorg-x11-fonts-misc
liberation-mono-fonts
liberation-narrow-fonts
liberation-narrow-fonts
liberation-sans-fonts
liberation-serif-fonts
glib2
If Arch Linux uses SELinux, you may also have to run this:
setsebool -P unconfirmed_chrome_sandbox_transition 0
It is also worth adding dumpio: true
to your options to debug. Should give you a more detailed output from puppeteer, instead of the generic error. As I mentioned in my comment. I have this option ignoreDefaultArgs: ['--disable-extensions']
. I can't tell you why because I don't remember. I think it is related to this issue, but also could be related to my corporate proxy.
QUESTION
In my script there are 5 different process which should work parallel. For now I am using multiprocessing pool method to run parallel processes. Actually it is working very well. But the problem is I want to use this script in a platform which has only 4 CPU. But this platform has also GPU (Nvidia Jetson Nano). So I want to run 4 process with CPUs and another one process should work with GPU. Let me explain with some code:
...ANSWER
Answered 2021-Nov-16 at 10:17GPU's cannot run Python. The actual object detection will be done in a non-Python function; likely a CUDA function (the native language of NVidia CPU's).
Since you have 4 CPU cores, the 5 threads will not run simultaneously. The "lock" code is also very suspect. In general, locks should be taken by the function that uses the variable, and the locks will prevent conflicts between multiple functions using the same variable. This requires that each function has a separate lock. counter_lock_1
outside any of the 5 process
functions is likely in the wrong place.
QUESTION
The code I work on has a substantial amount of floating point arithmetic in it. We have test cases that record the output for given inputs and verify that we don't change the results too much. I had it suggested that I enable -march native to improve performance. However, with that enabled we get test failures because the results have changed. Do the instructions that will be used because of access to more modern hardware enabled by -march native reduce the amount of floating point error? Increase the amount of floating point error? Or a bit of both? Fused multiply add should reduce the amount of floating point error but is that typical of instructions added over time? Or have some instructions been added that while more efficient are less accurate?
The platform I am targeting is x86_64 Linux. The processor information according to /proc/cpuinfo
is:
ANSWER
Answered 2021-Nov-15 at 09:40-march native
means -march $MY_HARDWARE
. We have no idea what hardware you have. For you, that would be -march=skylake-avx512
(SkyLake SP) The results could be reproduced by specifying your hardware architecture explicitly.
It's quite possible that the errors will decrease with more modern instructions, specifically Fused-Multiply-and-Add (FMA). This is the operation a*b+c, but rounded once instead of twice. That saves one rounding error.
QUESTION
hellow every one i migrated gitlab-ce into a new instance with new domain name using backup/restore
my problem : when i click a project it gives me "500 Whoops, something went wrong on our end "
i installed the same gitlab-ce version in the new host which is 13.6.2
my gitlab status
...ANSWER
Answered 2021-Oct-28 at 16:29To fix this problem I had to migrate gitlab-secrets.json
from /etc/gitlab
too, because this file contains the database encryption key, CI/CD variables, and variables used for two-factor authentication.
If you fail to restore this encryption key file along with the application data backup, users with two-factor authentication enabled and GitLab Runner lose access to your GitLab server.
QUESTION
I have a .csv file structured as well:
...ANSWER
Answered 2021-Oct-02 at 11:44Not sure how you want to present your output, but if you want to convert your string into list of integers list, just do:
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