19externunsignedlong__per_cpu_offset[NR_CPUS];2021#defineper_cpu_offset(x) (__per_cpu_offset[x])22#endif my_cpu_offset 30 ~ 37 ,利用 raw_smp_processor_id 得到 当前运行 cpu id [0,1,2,……] ,然后使用 per_cpu_offset 得到 当前cpu 变量区域 的offset . arch_raw_cpu_ptr(ptr) 43 ...
cpu = get_cpu(); y = per_cpu_ptr(&x, cpu); (*y)++; put_cpu(); 请注意,这些操作只能用于为特定处理器保留的per cpu数据。在周围代码中不禁用抢占的情况下,this_cpu_inc()只能保证正确递增一个per cpu计数器。但是,不能保证操作this_cpu指令执行之前或之后OS不会将进程移动。通常情况下,这意味着...
首先要考虑的是:在类对象本身当中不能存储类对象本身的 shared_ptr ,否则类对象 shared_ptr 永远也不会为0了,从而这些资源永远不会释放,除非程序结束。 其次:类对象肯定是外部函数通过某种机制分配的,而且一经分配立即交给 shared_ptr 管理( 再次强调一遍:给 shared_ptr 管理的资源必须在分配时交给 shared_ptr )...
unique_ptr weak_ptr auto_ptr(被 C++11 弃用)Class shared_ptr 实现共享式拥有(shared ownership)概念。多个智能指针指向相同对象,该对象和其相关资源会在 “最后一个 reference 被销毁” 时被释放。为了在结构较复杂的情景中执行上述工作,标准库提供 weak_ptr、bad_weak_ptr 和 enable_shared_from_this 等辅助...
Base *ptr = new Derived(); ptr->who(); // 因为Base有虚析构函数(virtual ~Base() {}),所以 delete 时,会先调用派生类(Derived)析构函数,再调用基类(Base)析构函数,防止内存泄漏。 delete ptr; ptr = nullptr; system("pause"); return 0; } volatile...
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run_metadata_ptr) File "D:\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1110, in _run feed_dict_tensor, options, run_metadata) File "D:\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1286, in _do_run ...
Apple is suggesting we create Ipv6 AAAA and PTR records for all our DCs. Is this the only solution and could it cause issues?AnswerThat’s not the first time Apple has had issues with .local domains and may not be your only problem (here, here, here, etc.). Moreover, it’s not ...
device.type != "cpu" else -1 streams = None if torch.cuda.is_available() and ctx.input_device == -1: # Perform CPU to GPU copies in a background stream # 新建 cuda stream streams = [_get_stream(device) for device in target_gpus] # 真正的操作 outputs = comm.scatter(input, ...
cpu G620双核:双开普通。三开顶不起。I3双核: 双开绝对稳定。三开普通 I5四核: 三开绝对稳定。四开顶不稳 I7四核: 五开绝对稳定。六开超稳。七开稳定性一般。八开请超频。AMD双核:4800+,卡机不解释。转道具吧 AMD双核:240,双开比较卡。AMD四核:双开绝对稳定。三开稳定。AMD六核:...