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llama.cpp
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Remove mutex for pipeline caches, since they are now per-thread.

This commit is contained in:
Nikhil Jain 2026-01-29 20:15:20 -08:00
parent d284baf1b5
commit 608fc9d16d
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1 changed files with 0 additions and 29 deletions
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29
ggml/src/ggml-webgpu/ggml-webgpu.cpp
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@ -861,9 +861,6 @@ static webgpu_command ggml_webgpu_pad(webgpu_context & ctx, ggml_tensor * src, g
};
webgpu_pipeline pipeline;
{
// TODO: remove guard once pipeline caches are per-thread
std::lock_guard<std::recursive_mutex> lock(ctx->global_ctx->mutex);
auto it = ctx->pad_pipelines.find(pipeline_key);
if (it != ctx->pad_pipelines.end()) {
pipeline = it->second;
@ -875,7 +872,6 @@ static webgpu_command ggml_webgpu_pad(webgpu_context & ctx, ggml_tensor * src, g
pipeline.context = processed.decisions;
ctx->pad_pipelines.emplace(pipeline_key, pipeline);
}
}
ggml_webgpu_generic_shader_decisions decisions =
*static_cast<ggml_webgpu_generic_shader_decisions *>(pipeline.context);
@ -944,9 +940,6 @@ static std::optional<webgpu_command> ggml_webgpu_set_rows(webgpu_context & ctx,
};
webgpu_pipeline pipeline;
// TODO: remove guard once pipeline caches are per-thread
{
std::lock_guard<std::recursive_mutex> lock(ctx->global_ctx->mutex);
auto it = ctx->set_rows_pipelines.find(key);
if (it != ctx->set_rows_pipelines.end()) {
pipeline = it->second;
@ -958,7 +951,6 @@ static std::optional<webgpu_command> ggml_webgpu_set_rows(webgpu_context & ctx,
pipeline.context = processed.decisions;
ctx->set_rows_pipelines.emplace(key, pipeline);
}
}
ggml_webgpu_generic_shader_decisions decisions =
*static_cast<ggml_webgpu_generic_shader_decisions *>(pipeline.context);
@ -1261,9 +1253,6 @@ static webgpu_command ggml_webgpu_flash_attn(webgpu_context & ctx,
};
webgpu_pipeline pipeline;
// TODO: remove guard once pipeline caches are per-thread
{
std::lock_guard<std::recursive_mutex> lock(ctx->global_ctx->mutex);
auto it = ctx->flash_attn_pipelines.find(key);
if (it != ctx->flash_attn_pipelines.end()) {
pipeline = it->second;
@ -1284,7 +1273,6 @@ static webgpu_command ggml_webgpu_flash_attn(webgpu_context & ctx,
pipeline.context = processed.decisions;
ctx->flash_attn_pipelines.emplace(key, pipeline);
}
}
ggml_webgpu_flash_attn_shader_decisions decisions =
*static_cast<ggml_webgpu_flash_attn_shader_decisions *>(pipeline.context);
@ -1308,9 +1296,6 @@ static webgpu_command ggml_webgpu_unary_op(webgpu_context & ctx, ggml_tensor * s
};
webgpu_pipeline pipeline;
{
// TODO: remove guard once pipeline caches are per-thread
std::lock_guard<std::recursive_mutex> lock(ctx->global_ctx->mutex);
auto it = ctx->unary_pipelines.find(pipeline_key);
if (it != ctx->unary_pipelines.end()) {
pipeline = it->second;
@ -1322,7 +1307,6 @@ static webgpu_command ggml_webgpu_unary_op(webgpu_context & ctx, ggml_tensor * s
pipeline.context = processed.decisions;
ctx->unary_pipelines.emplace(pipeline_key, pipeline);
}
}
ggml_webgpu_generic_shader_decisions decisions =
*static_cast<ggml_webgpu_generic_shader_decisions *>(pipeline.context);
@ -1743,9 +1727,6 @@ static webgpu_command ggml_webgpu_argmax(webgpu_context & ctx, ggml_tensor * src
};
webgpu_pipeline pipeline;
{
// TODO: remove guard once pipeline caches are per-thread
std::lock_guard<std::recursive_mutex> lock(ctx->global_ctx->mutex);
auto it = ctx->argmax_pipelines.find(shader_lib_ctx.vec4);
if (it != ctx->argmax_pipelines.end()) {
pipeline = it->second;
@ -1756,7 +1737,6 @@ static webgpu_command ggml_webgpu_argmax(webgpu_context & ctx, ggml_tensor * src
ggml_webgpu_create_pipeline(ctx->global_ctx->device, processed.wgsl.c_str(), processed.variant.c_str());
ctx->argmax_pipelines.emplace(shader_lib_ctx.vec4, pipeline);
}
}
uint32_t wg_x = ggml_nelements(dst);
return ggml_backend_webgpu_build(ctx->global_ctx, ctx->param_buf_pool, pipeline, params, entries, wg_x);
}
@ -1772,7 +1752,6 @@ static webgpu_command ggml_webgpu_argsort(webgpu_context & ctx, ggml_tensor * sr
.order = order
};
std::lock_guard<std::recursive_mutex> lock(ctx->global_ctx->mutex);
webgpu_pipeline argsort_pipeline;
auto it = ctx->argsort_pipelines.find(order);
if (it != ctx->argsort_pipelines.end()) {
@ -1963,9 +1942,6 @@ static webgpu_command ggml_webgpu_cumsum(webgpu_context & ctx, ggml_tensor * src
.max_wg_size = ctx->global_ctx->capabilities.limits.maxComputeInvocationsPerWorkgroup,
};
webgpu_pipeline pipeline;
// TODO: remove guard once pipeline caches are per-thread
{
std::lock_guard<std::recursive_mutex> lock(ctx->global_ctx->mutex);
auto it = ctx->cumsum_pipelines.find(1);
if (it != ctx->cumsum_pipelines.end()) {
pipeline = it->second;
@ -1976,7 +1952,6 @@ static webgpu_command ggml_webgpu_cumsum(webgpu_context & ctx, ggml_tensor * src
ggml_webgpu_create_pipeline(ctx->global_ctx->device, processed.wgsl.c_str(), processed.variant.c_str());
ctx->cumsum_pipelines.emplace(1, pipeline);
}
}
uint32_t wg_x = ggml_nrows(dst);
return ggml_backend_webgpu_build(ctx->global_ctx, ctx->param_buf_pool, pipeline, params, entries, wg_x);
}
@ -2009,9 +1984,6 @@ static webgpu_command ggml_webgpu_sum_rows(webgpu_context & ctx, ggml_tensor * s
};
webgpu_pipeline pipeline;
{
// TODO: remove guard once pipeline caches are per-thread
std::lock_guard<std::recursive_mutex> lock(ctx->global_ctx->mutex);
auto it = ctx->sum_rows_pipelines.find(1);
if (it != ctx->sum_rows_pipelines.end()) {
pipeline = it->second;
@ -2022,7 +1994,6 @@ static webgpu_command ggml_webgpu_sum_rows(webgpu_context & ctx, ggml_tensor * s
ggml_webgpu_create_pipeline(ctx->global_ctx->device, processed.wgsl.c_str(), processed.variant.c_str());
ctx->sum_rows_pipelines.emplace(1, pipeline);
}
}
uint32_t wg_x = total_sum ? 1 : ggml_nrows(dst);
return ggml_backend_webgpu_build(ctx->global_ctx, ctx->param_buf_pool, pipeline, params, entries, wg_x);
}