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author | Kawrakow <48489457+ikawrakow@users.noreply.github.com> | 2023-07-21 17:27:51 +0300 |
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committer | GitHub <noreply@github.com> | 2023-07-21 17:27:51 +0300 |
commit | d924522a46c5ef097af4a88087d91673e8e87e4d (patch) | |
tree | a78782f11a57de0633bed5e505666bef50a80901 | |
parent | 4d76a5f49b9b5382dba5d13d92edb9159536c225 (diff) |
Custom RoPE + bettter memory management for CUDA (#2295)
* Custom RoPE + bettter memory management for CUDA
* Adjusted look ahead in ggml_cuda_pool_malloc to 5%
This is sufficient it seems.
We end up using about 200 MB less VRAM that way when running
the 13B model with context 8192.
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
-rw-r--r-- | ggml-cuda.cu | 60 |
1 files changed, 49 insertions, 11 deletions
diff --git a/ggml-cuda.cu b/ggml-cuda.cu index 6537897..c07b546 100644 --- a/ggml-cuda.cu +++ b/ggml-cuda.cu @@ -2423,20 +2423,53 @@ static void * ggml_cuda_pool_malloc(size_t size, size_t * actual_size) { scoped_spin_lock lock(g_cuda_pool_lock); int id; CUDA_CHECK(cudaGetDevice(&id)); - +#ifdef DEBUG_CUDA_MALLOC + int nnz = 0; + size_t max_size = 0, tot_size = 0; +#endif + size_t best_diff = 1ull << 36; + int ibest = -1; for (int i = 0; i < MAX_CUDA_BUFFERS; ++i) { cuda_buffer& b = g_cuda_buffer_pool[id][i]; - if (b.size >= size && b.ptr != nullptr) { - void * ptr = b.ptr; - *actual_size = b.size; - b.ptr = nullptr; - b.size = 0; - return ptr; + if (b.ptr != nullptr) { +#ifdef DEBUG_CUDA_MALLOC + ++nnz; + tot_size += b.size; + if (b.size > max_size) max_size = b.size; +#endif + if (b.size >= size) { + size_t diff = b.size - size; + if (diff < best_diff) { + best_diff = diff; + ibest = i; + if (!best_diff) { + void * ptr = b.ptr; + *actual_size = b.size; + b.ptr = nullptr; + b.size = 0; + return ptr; + } + } + } } } + if (ibest >= 0) { + cuda_buffer& b = g_cuda_buffer_pool[id][ibest]; + void * ptr = b.ptr; + *actual_size = b.size; + b.ptr = nullptr; + b.size = 0; + return ptr; + } +#ifdef DEBUG_CUDA_MALLOC + fprintf(stderr, "%s: %d buffers, max_size = %u MB, tot_size = %u MB, requested %u MB\n", __func__, nnz, + (uint32_t)(max_size/1024/1024), (uint32_t)(tot_size/1024/1024), (uint32_t)(size/1024/1024)); +#endif void * ptr; - CUDA_CHECK(cudaMalloc((void **) &ptr, size)); - *actual_size = size; + size_t look_ahead_size = (size_t) (1.05 * size); + look_ahead_size = 256 * ((look_ahead_size + 255)/256); + CUDA_CHECK(cudaMalloc((void **) &ptr, look_ahead_size)); + *actual_size = look_ahead_size; return ptr; } @@ -2955,8 +2988,13 @@ inline void ggml_cuda_op_rope( const int mode = ((int32_t *) src1->data)[2]; const int n_ctx = ((int32_t *) src1->data)[3]; - const float theta_scale = powf(10000.0, -2.0f/n_dims); - const float p = ((mode & 1) == 0 ? n_past + i02 : i02); + // RoPE alteration for extended context + float freq_base, freq_scale; + memcpy(&freq_base, (int32_t *) src1->data + 4, sizeof(float)); + memcpy(&freq_scale, (int32_t *) src1->data + 5, sizeof(float)); + + const float theta_scale = powf(freq_base, -2.0f/n_dims); + const float p = (((mode & 1) == 0 ? n_past + i02 : i02)) * freq_scale; bool is_glm = mode & 4; |