hello, i wrote a method with Neon for accelerate my code.. I don't have the expected result only simples instructions and, or, shift... on 64bits no gain speed. nada :-( i dont understand... how programm this method for speed? original code : unsigned long long RXBitBoard::get_legal_moves(const unsigned long long p_discs, const unsigned long long o_discs) { const unsigned long long inner_o_discs = o_discs & 0x7E7E7E7E7E7E7E7EULL; /* direction W */ unsigned long long flipped = (p_discs >> 1) & inner_o_discs; flipped |= (flipped >> 1) & inner_o_discs; unsigned long long adjacent_o_discs = inner_o_discs & (inner_o_discs >> 1); flipped |= (flipped >> 2) & adjacent_o_discs; flipped |= (flipped >> 2) & adjacent_o_discs; unsigned long long legals = flipped >> 1; // /* direction _E*/ // flipped = (p_discs << 1) & inner_o_discs; // flipped |= (flipped << 1) & inner_o_discs; // // adjacent_o_discs = inner_o_discs & (inner_o_discs << 1); // // flipped |= (flipped << 2) & adjacent_o_discs; // flipped |= (flipped << 2) & adjacent_o_discs; // // legals |= flipped << 1; // trick /* direction _E */ flipped = (p_discs << 1); legals |= ((flipped + inner_o_discs) & ~flipped); /* direction S */ flipped = (p_discs >> 8) & o_discs; flipped |= (flipped >> 8) & o_discs; adjacent_o_discs = o_discs & (o_discs >> 8); flipped |= (flipped >> 16) & adjacent_o_discs; flipped |= (flipped >> 16) & adjacent_o_discs; legals |= flipped >> 8; /* direction N */ flipped = (p_discs << 8) & o_discs; flipped |= (flipped << 8) & o_discs; adjacent_o_discs = o_discs & (o_discs << 8); flipped |= (flipped << 16) & adjacent_o_discs; flipped |= (flipped << 16) & adjacent_o_discs; legals |= flipped << 8; /* direction NE */ flipped = (p_discs >> 7) & inner_o_discs; flipped |= (flipped >> 7) & inner_o_discs; adjacent_o_discs = inner_o_discs & (inner_o_discs >> 7); flipped |= (flipped >> 14) & adjacent_o_discs; flipped |= (flipped >> 14) & adjacent_o_discs; legals |= flipped >> 7; /* direction SW */ flipped = (p_discs << 7) & inner_o_discs; flipped |= (flipped << 7) & inner_o_discs; adjacent_o_discs = inner_o_discs & (inner_o_discs << 7); flipped |= (flipped << 14) & adjacent_o_discs; flipped |= (flipped << 14) & adjacent_o_discs; legals |= flipped << 7; /* direction NW */ flipped = (p_discs >> 9) & inner_o_discs; flipped |= (flipped >> 9) & inner_o_discs; adjacent_o_discs = inner_o_discs & (inner_o_discs >> 9); flipped |= (flipped >> 18) & adjacent_o_discs; flipped |= (flipped >> 18) & adjacent_o_discs; legals |= flipped >> 9; /* direction SE */ flipped = (p_discs << 9) & inner_o_discs; flipped |= (flipped << 9) & inner_o_discs; adjacent_o_discs = inner_o_discs & (inner_o_discs << 9); flipped |= (flipped << 18) & adjacent_o_discs; flipped |= (flipped << 18) & adjacent_o_discs; legals |= flipped << 9; //Removes existing discs legals &= ~(p_discs | o_discs); return legals; } my neon code const uint64x2_t pp_discs = vdupq_n_u64(p_discs); const uint64x2_t oo_discs = vdupq_n_u64(o_discs); const uint64x2_t inner_oo_discs = vdupq_n_u64(o_discs & 0x7E7E7E7E7E7E7E7EULL); //horizontals directions -1, +1 static const int64x2_t shift_1 = {-1, 1}; static const int64x2_t shift_2 = {-2, 2}; uint64x2_t flipped = vandq_u64(vshlq_u64(pp_discs, shift_1), inner_oo_discs); flipped = vorrq_u64(flipped, vandq_u64(vshlq_u64(flipped, shift_1), inner_oo_discs)); uint64x2_t adjacent_oo_discs = vandq_u64(inner_oo_discs, vshlq_u64(inner_oo_discs, shift_1)); flipped = vorrq_u64(flipped, vandq_u64(vshlq_u64(flipped, shift_2), adjacent_oo_discs)); flipped = vorrq_u64(flipped, vandq_u64(vshlq_u64(flipped, shift_2), adjacent_oo_discs)); uint64x2_t legals = vshlq_u64(flipped, shift_1); //verticals directions -8 , +8 static const int64x2_t shift_8 = {-8, 8}; static const int64x2_t shift_16 = {-16, 16}; flipped = vandq_u64(vshlq_u64(pp_discs, shift_8), oo_discs); flipped = vorrq_u64(flipped, vandq_u64(vshlq_u64(flipped, shift_8), oo_discs)); adjacent_oo_discs = vandq_u64(oo_discs, vshlq_u64(oo_discs, shift_8)); flipped = vorrq_u64(flipped, vandq_u64(vshlq_u64(flipped, shift_16), adjacent_oo_discs)); flipped = vorrq_u64(flipped, vandq_u64(vshlq_u64(flipped, shift_16), adjacent_oo_discs)); legals = vorrq_u64(legals, vshlq_u64(flipped, shift_8)); //diagonals directions -7 , +7 static const int64x2_t shift_7 = {-7, 7}; static const int64x2_t shift_14 = {-14, 14}; flipped = vandq_u64(vshlq_u64(pp_discs, shift_7), inner_oo_discs); flipped = vorrq_u64(flipped, vandq_u64(vshlq_u64(flipped, shift_7), inner_oo_discs)); adjacent_oo_discs = vandq_u64(inner_oo_discs, vshlq_u64(inner_oo_discs, shift_7)); flipped = vorrq_u64(flipped, vandq_u64(vshlq_u64(flipped, shift_14), adjacent_oo_discs)); flipped = vorrq_u64(flipped, vandq_u64(vshlq_u64(flipped, shift_14), adjacent_oo_discs)); legals = vorrq_u64(legals, vshlq_u64(flipped, shift_7)); //diagonals directions -9 , +9 static const int64x2_t shift_9 = {-9, 9}; static const int64x2_t shift_18 = {-18, 18}; flipped = vandq_u64(vshlq_u64(pp_discs, shift_9), inner_oo_discs); flipped = vorrq_u64(flipped, vandq_u64(vshlq_u64(flipped, shift_9), inner_oo_discs)); adjacent_oo_discs = vandq_u64(inner_oo_discs, vshlq_u64(inner_oo_discs, shift_9)); flipped = vorrq_u64(flipped, vandq_u64(vshlq_u64(flipped, shift_18), adjacent_oo_discs)); flipped = vorrq_u64(flipped, vandq_u64(vshlq_u64(flipped, shift_18), adjacent_oo_discs)); legals = vorrq_u64(legals, vshlq_u64(flipped, shift_9)); return ((vgetq_lane_u64(legals, 0) | vgetq_lane_u64(legals, 1)) & ~(p_discs | o_discs)); } i even wrote a interleave version I can expect a speed gain, no?

I have an Intel based Macbook Pro, which I use for iOS development. Recently I have the need to test my apps on M-series Apple Silicon based simulator images (specifically, 13 inch versions of iPads) which have no "A" series equivalent (iPad Air 13, iPad Pro 13, etc). I have "created" simulators for these devices in Xcode Simulators and Devices, but they do never appear under the File > Open Simulator menu. I have confirmed that creating a new simulator with any A-class device does not exhibit this issue. Interestingly, these device types do NOT appear under the same "Device Type" menu when attempting to create a "New Simulator" from within the Simulator itself. Creating a Simulator in "Device and Simulators" The same menu from inside the "Simulator" app - missing M-class devices: Can anyone confirm, preferably with a link to the documentation, that this is intended behavior? Apple expects us to support M class devices, on still-supported Intel devices, without access to appropriate simulators? Or is this just my machine? System: 16-inch, 2019 MacBook Pro Sonoma 14.0 Xcode 15.4 (15F31d) Thank you

Investigating a kernel panic, I discovered that Apple Silicon Panic traces are not working with how I know to symbolicate the panic information. I have not found proper documentation that corrects this situation. Attached file is an indentity-removed panic, received from causing an intentional panic (dereferencing nullptr), so that I know what functions to expect in the call stack. This is cut-and-pasted from the "Report To Apple" dialog that appears after the reboot: panic_1_4_21_b.txt To start, I download and install the matching KDK (in this case KDK_14.6.1_23G93.kdk), identified from this line: OS version: 23G93 Kernel version: Darwin Kernel Version 23.6.0: Mon Jul 29 21:14:04 PDT 2024; root:xnu-10063.141.2~1/RELEASE_ARM64_T8122 Then start lldb from Terminal, using this command: bash_prompt % lldb -arch arm64e /Library/Developer/KDKs/KDK_14.6.1_23G93.kdk/System/Library/Kernels/kernel.release.t8122 Next I load the remaining scripts per the instructions from lldb: (lldb) settings set target.load-script-from-symbol-file true I need to know what address to load my kext symbols to, which I read from this line of the panic log, after the @ symbol: com.company.product(1.4.21d119)[92BABD94-80A4-3F6D-857A-3240E4DA8009]@0xfffffe001203bfd0->0xfffffe00120533ab I am using a debug build of my kext, so the DWARF symbols are part of the binary. I use this line to load the symbols into the lldb session: (lldb) addkext -F /Library/Extensions/KextName.kext/Contents/MacOS/KextName 0xfffffe001203bfd0 And now I should be able to use lldb image lookup to identify pointers on the stack that land within my kext. For example, the current PC at the moment of the crash lands within the kext (expected, because it was intentional): (lldb) image lookup -a 0xfffffe001203fe10 Which gives the following incorrect result: Address: KextName[0x0000000000003e40] (KextName.__TEXT.__cstring + 14456) Summary: "ffer has %d retains\n" That's not even a program instruction - that's within a cstring. No, that cstring isn't involved in anything pertaining to the intentional panic I am expecting to see. Can someone please explain what I'm doing wrong and provide instructions that will give symbol information from a panic trace on an Apple Silicon Mac? Disclaimers: Yes I know IOPCIFamily is deprecated, I am in process of transitioning to DriverKit Dext from IOKit kext. Until then I must maintain the kext. Terminal command "atos" provides similar incorrect results, and seems to not work with debug-built-binaries (only dSYM files) Yes this is an intentional panic so that I can verify the symbolicate process before I move on to investigating an unexpected panic I have set nvram boot-args to include keepsyms=1 I have tried (lldb) command script import lldb.macosx but get a result of error: no images in crash log (after the nvram settings)

I want to get MacOS Version from Objective-C build for iOS Apps to run on Apple Silicon Mac. Because AppStore In-App Purchase on Apple Silicon Mac had issues on MacOS version 13.0 and was fixed at version 13.3.1. I need to know the exact version of the MacOS to prevent users from buying In-App Purchases. I found that I can get iOS version that the app is emulating on and assume MacOS version from iOS version. But I think it's not 100% guaranteed way, because no documentation says anything about it. Is there a way to get MacOS Version in iOS Apps running on Apple Silicon Mac?

Helpppp. I installed Krita from the Appstore, it works. Then install ai_diffusion and I got : xcrun: error: cannot be used within an App Sandbox. Can anybody help me? Thanks. AttributeError Python 3.10.7: /Applications/krita.app/Contents/MacOS/krita Sat Aug 3 18:15:59 2024 A problem occurred in a Python script. Here is the sequence of function calls leading up to the error, in the order they occurred. /Users/alejandropereira/Library/Containers/org.kde.krita/Data/Library/Application Support/krita/pykrita/ai_diffusion/ui/region.py in update_settings(self=<ai_diffusion.ui.region.ActiveRegionWidget object>, key='prompt_translation', value=None) 345 self._layout_language_button() 346 elif key == "prompt_translation": 347 self._update_language() 348 349 async def _replace_with_translation(self, client: Client): self = <ai_diffusion.ui.region.ActiveRegionWidget object> self._update_language = > /Users/alejandropereira/Library/Containers/org.kde.krita/Data/Library/Application Support/krita/pykrita/ai_diffusion/ui/region.py in _update_language(self=<ai_diffusion.ui.region.ActiveRegionWidget object>) 381 enabled = self._root._model.translation_enabled 382 lang = settings.prompt_translation if enabled else "en" 383 self._language_button.setText(lang.upper()) 384 if enabled: 385 text = self._lang_help_enabled self = <ai_diffusion.ui.region.ActiveRegionWidget object> self._language_button = <PyQt5.QtWidgets.QToolButton object> self._language_button.setText = lang = None lang.upper undefined AttributeError: 'NoneType' object has no attribute 'upper' cause = None class = <class 'AttributeError'> context = None delattr = <method-wrapper 'delattr' of AttributeError object> dict = {} dir = doc = 'Attribute not found.' eq = <method-wrapper 'eq' of AttributeError object> format = ge = <method-wrapper 'ge' of AttributeError object> getattribute = <method-wrapper 'getattribute' of AttributeError object> gt = <method-wrapper 'gt' of AttributeError object> hash = <method-wrapper 'hash' of AttributeError object> init = <method-wrapper 'init' of AttributeError object> init_subclass = le = <method-wrapper 'le' of AttributeError object> lt = <method-wrapper 'lt' of AttributeError object> ne = <method-wrapper 'ne' of AttributeError object> new = reduce = reduce_ex = repr = <method-wrapper 'repr' of AttributeError object> setattr = <method-wrapper 'setattr' of AttributeError object> setstate = sizeof = str = <method-wrapper 'str' of AttributeError object> subclasshook = suppress_context = False traceback = args = ("'NoneType' object has no attribute 'upper'",) name = 'upper' obj = None with_traceback = The above is a description of an error in a Python program. Here is the original traceback: Traceback (most recent call last): File "/Users/alejandropereira/Library/Containers/org.kde.krita/Data/Library/Application Support/krita/pykrita/ai_diffusion/ui/region.py", line 347, in update_settings self._update_language() File "/Users/alejandropereira/Library/Containers/org.kde.krita/Data/Library/Application Support/krita/pykrita/ai_diffusion/ui/region.py", line 383, in _update_language self._language_button.setText(lang.upper()) AttributeError: 'NoneType' object has no attribute 'upper'

Recently I started getting emails from AppStoreConnect when I submit new builds The email states: ITMS-90863: Macs with Apple silicon support issue - The app links with libraries that aren’t present in macOS: /usr/lib/swift/libswiftCloudKit.dylib I can run this app on apple silicon from TestFlight or directly from Xcode and it runs just fine including all iCloud functions. This app has been using iCloud for several years now. So my question is: Should I just ignore the email or do I need to change something to bring this app into compliance?

Hello, I have an iOS app that is recording audio that is working fine on iPads/iPhones. It asks for microphone permission and after that recording works. I installed the same app on my M3 MacBook via TestFlight since iPad apps are supposed to work without a change that way. The app starts fine and everything, but it never asks for Microphone permission, so I can't record. Do I need to do something to make this happen (this is not macCatalyst, its running the arm64 iPhone binary on macOS) thanks

It seems that Xcode Cloud currently only uses Intel machines for running the workflow jobs. When will Apple Silicon machines be available and supported?

Call to std::remainder(double(411.0), int(365)); results in a crash due to a nan in libsystem_m.dylib. MCVE program is provided + lldb backtrace and system report. $ clang++ -g -arch arm64 -std=c++20 main.cpp -o test $ ./test ori_fpcr=0, new_fpcr=1792 std::fmod(simTimeInDays, numDays) = 46 Illegal instruction: 4 main.cpp #include <cassert> #include <cfenv> #include <cmath> #include <iostream> #if !defined(__arm64__) || !defined(__APPLE__) # error "Meant to be run on arm64 apple" #endif inline int feenableexcept(unsigned int excepts) { static fenv_t fenv; if (std::fegetenv(&fenv) != 0) { return -1; } const unsigned long long old_fpcr = fenv.__fpcr; const unsigned int old_excepts = (old_fpcr >> 8u) & unsigned(FE_ALL_EXCEPT); // Check the bits passed are valid, and bit shift them const unsigned int new_excepts = excepts & unsigned(FE_ALL_EXCEPT); const unsigned long long new_fpcr = new_excepts << 8u; // Set the new bits fenv.__fpcr = fenv.__fpcr | new_fpcr; return (std::fesetenv(&fenv) != 0) ? -1 : static_cast<int>(old_excepts); } int main([[maybe_unused]] int argc, [[maybe_unused]] const char** argv) { constexpr unsigned int flags = FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW; static_assert(flags == 7); constexpr uint32_t fpcr_flags_shifted = flags << 8; constexpr uint32_t fpcr_flags = (__fpcr_trap_divbyzero | __fpcr_trap_invalid | __fpcr_trap_overflow); static_assert(fpcr_flags_shifted == fpcr_flags); static_assert(fpcr_flags_shifted == 1792); uint32_t ori_fpcr = __builtin_arm_rsr("fpcr"); feenableexcept(flags); uint32_t new_fpcr = __builtin_arm_rsr("fpcr"); // std::cout << "(FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW) = " << flags << '\n'; // std::cout << "((FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW) << 8) = " << fpcr_flags_shifted << '\n'; // std::cout << "(__fpcr_trap_divbyzero | __fpcr_trap_invalid | __fpcr_trap_overflow) = " << fpcr_flags << '\n'; std::cout << "ori_fpcr=" << ori_fpcr << ", new_fpcr=" << new_fpcr << '\n'; const double simTimeInDays = 411.0; const int numDays = 365; // This is fine std::cout << "std::fmod(simTimeInDays, numDays) = " << std::fmod(simTimeInDays, numDays) << '\n'; // This isn't std::cout << "std::fmod(simTimeInDays, numDays) = " << std::remainder(simTimeInDays, numDays) << '\n'; return 0; } backtrace: see attachment lldb_backtrace.txt $ system_profiler SPSoftwareDataType SPHardwareDataType Software: System Software Overview: System Version: macOS 13.2 (22D49) Kernel Version: Darwin 22.3.0 Boot Volume: Macintosh HD Boot Mode: Normal Secure Virtual Memory: Enabled System Integrity Protection: Enabled Time since boot: 7 hours, 58 minutes Hardware: Hardware Overview: Model Name: MacBook Pro Model Identifier: MacBookPro18,2 Model Number: Z14V000NBFN/A Chip: Apple M1 Max Total Number of Cores: 10 (8 performance and 2 efficiency) Memory: 64 GB System Firmware Version: 8419.80.7 OS Loader Version: 8419.80.7 Activation Lock Status: Enabled $ otool -L test test: /usr/lib/libc++.1.dylib (compatibility version 1.0.0, current version 1300.36.0) /usr/lib/libSystem.B.dylib (compatibility version 1.0.0, current version 1319.0.0 $ clang++ --version Apple clang version 14.0.0 (clang-1400.0.29.202) Target: arm64-apple-darwin22.3.0 Thread model: posix InstalledDir: /Library/Developer/CommandLineTools/usr/bin

I'm using M1pro and have successfully installed Numpy with Accelerate following, and it really speedup my programs. I also ran np.test() to check the correctness and every test passed. However, I can't install Scipy with Accelerate, since the official document said Accelerate has a LAPACK of too old version. I can't even find a scipy that can pass scipy.test(). I tried the codes below: conda install numpy 'libblas=*=*accelerate' conda install scipy np.test() as fails, sp.test() can't even finish conda install numpy 'libblas=*=*openblas' conda install scipy Both np.test() and sp.test() can finish, but with many failures. I believe the bugs are due to Conda. pip install --no-binary :all: --no-use-pep517 numpy pip install scipy np.test() has no failure and went fast, sp.test() uses OpenBLAS and has 3 failures. This is the best version I have found. So my question is: can we find a reliable version of scipy on M1? Considering the popularity of scipy, I think it's not a high-living expectation. And a question for Apple: is there really a plan to upgrade the LAPACK in Accelerate?