per_process_gpu_memory_fraction:double,分配给每个进程的可用 GPU 内存的一部分。 1 表示分配所有 GPU 内存,0.5 表示进程分配高达 ~50% 的可用 GPU 内存。 除非启用了allow_growth选项,否则会预先分配 GPU 内存。 如果大于 1.0,则使用 CUDA 统一内存通过将主机内存用作交换空间来潜在的超额使用 GPU 设备上的可...
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Using tfjs-node-gpu on a GKE cluster running on an n1-higmem-8 with an NVIDIA P4 or V100 GPU fails when the cuda_malloc_async allocater is set using TF_GPU_ALLOCATOR. System information Have I written custom code (as opposed to using a s...
session = tf.Session(config=config) 方式二: gpu_options=tf.GPUOptions(per_process_gpu_memory_fraction=0.85) config=tf.ConfigProto(gpu_options=gpu_options) session = tf.Session(config=config) tf.GPUOptions可用的设置项有: per_process_gpu_memory_fraction # allocator_type # deferred_deletion_bytes...
先来看一下 TF 内存的分配机制,TF 的 GPU 显存是通过 BFC (best-fit with coalescing) 算法来分配的,CPU 内存分配是直接调用底层 glibc ptmalloc2 的 memory allocation。 目前平台上 CTR 类业务基本都是 CPU 推理,因此内存的分配和释放都是通过 glibc ptmalloc2 来管理的。
<long, std::__ndk1::allocator<long> > const&, absl::lts_20230125::Status (tflite::gpu::InferenceRunner::*)(int, std::__ndk1::variant<std::__ndk1::monostate, tflite::gpu::OpenGlBuffer, tflite::gpu::OpenGlTexture, tflite::gpu::CpuMemory, tflite::gpu::OpenClBuffer, tflite::...
config.gpu_options.allocator_type = 'BFC' sess = tf.Session(config=config) sess.run(init) time_tensorflow_run(sess, predictions, {keep_prob:1.0}, "Forward") objective = tf.nn.l2_loss(fc8) grad = tf.gradients(objective, p) time_tensorflow_run(sess, grad, {keep_prob:0.5}, "Forward...
10:54.736610: W external/org_tensorflow/tensorflow/core/common_runtime/bfc_allocator.cc:211] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.26GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available...
allocator_type string allocator_type allow_growth bool allow_growth deferred_deletion_bytes int64 deferred_deletion_bytes experimental Experimental experimental force_gpu_compatible bool force_gpu_compatible per_process_gpu_memory_fraction double per_process_gpu_memory_fraction ...
config.gpu_options.allocator_type='BFC'