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authorMitja Felicijan <mitja.felicijan@gmail.com>2026-02-12 20:57:17 +0100
committerMitja Felicijan <mitja.felicijan@gmail.com>2026-02-12 20:57:17 +0100
commitb333b06772c89d96aacb5490d6a219fba7c09cc6 (patch)
tree211df60083a5946baa2ed61d33d8121b7e251b06 /llama.cpp/ggml/src/ggml-cuda/arange.cu
downloadllmnpc-b333b06772c89d96aacb5490d6a219fba7c09cc6.tar.gz
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Diffstat (limited to 'llama.cpp/ggml/src/ggml-cuda/arange.cu')
-rw-r--r--llama.cpp/ggml/src/ggml-cuda/arange.cu34
1 files changed, 34 insertions, 0 deletions
diff --git a/llama.cpp/ggml/src/ggml-cuda/arange.cu b/llama.cpp/ggml/src/ggml-cuda/arange.cu
new file mode 100644
index 0000000..b5e495a
--- /dev/null
+++ b/llama.cpp/ggml/src/ggml-cuda/arange.cu
@@ -0,0 +1,34 @@
+#include "arange.cuh"
+
+static __global__ void arange_f32(float * dst, const int ne0, const float start, const float step) {
+ // blockIDx.x: idx of ne0 / BLOCK_SIZE
+ int nidx = threadIdx.x + blockIdx.x * blockDim.x;
+ if (nidx >= ne0) {
+ return;
+ }
+ dst[nidx] = start + step * nidx;
+}
+
+static void arange_f32_cuda(float * dst, const int ne0, const float start, const float step, cudaStream_t stream) {
+ int num_blocks = (ne0 + CUDA_ARANGE_BLOCK_SIZE - 1) / CUDA_ARANGE_BLOCK_SIZE;
+ arange_f32<<<num_blocks, CUDA_ARANGE_BLOCK_SIZE, 0, stream>>>(dst, ne0, start, step);
+}
+
+void ggml_cuda_op_arange(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
+ float * dst_d = (float *)dst->data;
+ cudaStream_t stream = ctx.stream();
+
+ GGML_ASSERT(dst->type == GGML_TYPE_F32);
+
+ float start;
+ float stop;
+ float step;
+ memcpy(&start, (float *)dst->op_params + 0, sizeof(float));
+ memcpy(&stop, (float *)dst->op_params + 1, sizeof(float));
+ memcpy(&step, (float *)dst->op_params + 2, sizeof(float));
+
+ int64_t steps = (int64_t)ceil((stop - start) / step);
+ GGML_ASSERT(ggml_nelements(dst) == steps);
+
+ arange_f32_cuda(dst_d, dst->ne[0], start, step, stream);
+}