https://github.com/cjmcv/pocket-ai

• engine/cl: A small computing framework based on opencl. This framework is designed to help you quickly call Opencl API to do the calculations you need.

• engine/vk: A small computing framework based on vulkan. This framework is designed to help you quickly call vulkan's computing API to do the calculations you need.

• engine/graph: A small multitasking scheduler that can quickly build efficient pipelines for your multiple tasks.

• engine/infer: A tiny inference engine for microprocessors, with a library size of only 10K+.

• eval/llm: A small tool is used to quickly verify whether the end-to-end calculation results are correct when accelerating and optimizing the large language model (LLM) inference engine.

• Other small tools.

https://github.com/cjmcv/hpc/tree/master/0-frameworks/cux

tag: cuda / simd / openmp.

https://github.com/cjmcv/hpc/tree/master/0-frameworks/mrpc

tag: distributed computing.

• base_graph : Record the basic usage of cuda graph.
• base_unified_memory : A simple task consumer using threads and streams with all data in Unified Memory.
• base_zero_copy : Zero Copy.
• gemm_fp16_wmma : Gemm fp16 - wmma
• gemm_fp32 : Gemm fp32 - cuda core
• reduce_fp32.cu : Based on warp reduce.
• marlin_kernel : Reading notes on the Marlin Kernel.

• gemm_fp32 : Gemm fp32.

• basic_demo : Introduce the basic calling method and process of OpenCL API (without using pocket-ai).
• gemm_f32 : Gemm fp32 for Discrete graphics card.
• gemm_mobile_f32 : Gemm fp32 for integrated graphics card.

• gemm_fp32 : Gemm fp32.
• gemm_int8 : Gemm int8.
• matrix_transpose : Matrix Transpose.

• linear : Linear operator (fp32/bf16/int8)
• matrix_transpose : Matrix Transpose (int32/fp32)
• vector_scan : Scan. Prefix Sum.

• alg_matrix_multiply : gemm: C = A * B.
• base_broadcast_scatter_gather : Record the basic usage of Bcast, Scatter, Gather and Allgather.
• base_group : Group communication.
• base_hello_world : Environment Management Routines.
• base_reduce_alltoall_scan : Record the basic usage of Reduce, Allreduce, Alltoall, Scan and Exscan.
• base_send_recv : Record the basic usage of MPI_Send/MPI_Recv and MPI_ISend/MPI_IRecv.
• base_type_contiguous : Send and receive custom types of data by using MPI_Type_contiguous.
• base_type_struct : Send and receive custom types of data by using MPI_Type_struct.
• util_bandwidth_test : Test bandwidth by point-to-point communications.
• py_base_broadcast_scatter_gather : Record the basic usage of Bcast, Scatter, Gather and Allgather.
• py_base_reduce_scan : Record the basic usage of Reduce and Scan.
• py_base_send_recv : Record the basic usage of Send and Recv.

• alg_quick_sort: Quick sort using std::thread.
• alg_vector_dot_product: Vector dot product: h_result = SUM(A * B). Record the basic usage of std::tread and std::sync.
• base_async: Record the basic usage of std::async.
• util_blocking_queue: Blocking queue. Mainly implemented by thread, queue and condition_variable.
• util_internal_thread: Internal Thread. Mainly implemented by std::thread.
• util_thread_pool: Thread Pool. Mainly implemented by thread, queue, future and condition_variable.

• alg_matrix_multiply : gemm: C = A * B.
• alg_pi_calculate : Calculate PI using parallel, for and reduction.
• base_flush : Records the basic usage of flush.
• base_mutex : Mutex operation in openmp, including critical, atomic, lock.
• base_parallel_for : Parallel and For.
• base_schedule : Records the basic usage of schedule.
• base_sections_single : Records the basic usage of Sections and Single.
• base_synchronous : Synchronous operation in openmp, including barrier, ordered and master.

• base_allocator : The basic use of allocator.
• base_atomic : The basic use of atomic.
• base_concurrent_hash_map : The basic use of concurrent_hash_map.
• base_concurrent_queue : The basic use of concurrent queue.
• base_mutex : The basic use of mutex in tbb.
• base_parallel_for : The basic use of parallel_for.
• base_parallel_reduce : The basic use of parallel_reduce.
• base_parallel_scan : The basic use of parallel_scan.
• base_parallel_sort : The basic use of base_parallel_sort.
• base_task_scheduler : The basic use of base_task_scheduler.
• count_strings : Count strings. Use the concurrent_hash_map.

• base_future: Record the basic usage of future.
• base_gather: Use gather to execute tasks in parallel.
• base_hello_world: Hello world. Record the basic usage of async, await and loop.
• base_loop_chain: Executes nested coroutines.