# Go to hipBLASLt build directory
cd hipBLASLt; cd build/release
# run hipblaslt-bench
./clients/staging/hipblaslt-bench --help
./clients/staging/hipblaslt-bench [ --data <path> | --yaml <path> ] <options> ...
--sizem |-m <value> Specific matrix size: the number of rows or columns in matrix. (Default value is: 128)
--sizen |-n <value> Specific matrix the number of rows or columns in matrix (Default value is: 128)
--sizek |-k <value> Specific matrix size: the number of columns in A and rows in B. (Default value is: 128)
--lda <value> Leading dimension of matrix A.
--ldb <value> Leading dimension of matrix B.
--ldc <value> Leading dimension of matrix C.
--ldd <value> Leading dimension of matrix D.
--lde <value> Leading dimension of matrix E.
--any_stride Do not modify input strides based on leading dimensions
--stride_a <value> Specific stride of strided_batched matrix A, second dimension * leading dimension.
--stride_b <value> Specific stride of strided_batched matrix B, second dimension * leading dimension.
--stride_c <value> Specific stride of strided_batched matrix C, second dimension * leading dimension.
--stride_d <value> Specific stride of strided_batched matrix D, second dimension * leading dimension.
--stride_e <value> Specific stride of strided_batched matrix E, second dimension * leading dimension.
--alpha <value> specifies the scalar alpha (Default value is: 1)
--beta <value> specifies the scalar beta (Default value is: 0)
--function |-f <value> BLASLt function to test. Options: matmul (Default value is: matmul)
--precision |-r <value> Precision of matrix A,B,C,D Options: f32_r,f16_r,bf16_r,f64_r,i32_r,i8_r (Default value is: f16_r)
--a_type <value> Precision of matrix A. Options: f32_r,f16_r,bf16_r,i8_r
--b_type <value> Precision of matrix B. Options: f32_r,f16_r,bf16_r,i8_r
--c_type <value> Precision of matrix C. Options: f32_r,f16_r,bf16_r,i8_r
--d_type <value> Precision of matrix D. Options: f32_r,f16_r,bf16_r,i8_r
--compute_type <value> Precision of computation. Options: s,f32_r,x,xf32_r,f64_r,i32_r (Default value is: f32_r)
--compute_input_typeA <value> Options: f32_r, f16_r, bf16_r, f8_r, bf8_r, The default value indicates that the argument has no effect. (Default value is: INVALID)
--compute_input_typeB <value> Options: f32_r, f16_r, bf16_r, f8_r, bf8_r, The default value indicates that the argument has no effect. (Default value is: INVALID)
--scale_type <value> Precision of scalar. Options: f16_r,bf16_r
--initialization <value> Initialize matrix data.Options: rand_int, trig_float, hpl(floating), special, zero (Default value is: hpl)
--transA <value> N = no transpose, T = transpose, C = conjugate transpose (Default value is: N)
--transB <value> N = no transpose, T = transpose, C = conjugate transpose (Default value is: N)
--batch_count <value> Number of matrices. Only applicable to batched and strided_batched routines (Default value is: 1)
--HMM Parameter requesting the use of HipManagedMemory
--verify |-v Validate GPU results with CPU?
--iters |-i <value> Iterations to run inside timing loop (Default value is: 10)
--cold_iters |-j <value> Cold Iterations to run before entering the timing loop (Default value is: 2)
--algo_method <value> Use different algorithm search API. Options: heuristic, all, index. (Default value is: heuristic)
--solution_index <value> Used with --algo_method 2. Specify solution index to use in benchmark. (Default value is: -1)
--requested_solution <value> Requested solution num. Set to -1 to get all solutions. Only valid when algo_method is set to heuristic. (Default value is: 1)
--activation_type <value> Options: None, gelu, relu (Default value is: none)
--activation_arg1 <value> Reserved. (Default value is: 0)
--activation_arg2 <value> Reserved. (Default value is: inf)
--bias_type <value> Precision of bias vector.Options: f16_r,bf16_r,f32_r,default(same with D type)
--bias_source <value> Choose bias source: a, b, d (Default value is: d)
--bias_vector Apply bias vector
--scaleA Apply scale for A buffer
--scaleB Apply scale for B buffer
--scaleAlpha_vector Apply scaleAlpha vector
--amaxScaleA Apple scale for A buffer by abs max of A buffer
--amaxScaleB Apple scale for B buffer by abs max of B buffer
--use_e Apply AUX output/ gradient input
--gradient Enable gradient
--grouped_gemm Use grouped_gemm.
--use_user_args Use UserArguments located in device memory for grouped gemm.
--device <value> Set default device to be used for subsequent program runs (Default value is: 0)
--c_equal_d C and D are stored in same memory
--workspace <value> Set fixed workspace memory size instead of using hipblaslt managed memory (Default value is: 0)
--log_function_name Function name precedes other items.
--function_filter <value> Simple strstr filter on function name only without wildcards
--api_method <value> Use extension API. c: C style API. mix: declaration with C hipblasLtMatmul Layout/Desc but set, initialize, and run the problem with C++ extension API. cpp: Using C++ extension API only. Options: c, mix, cpp. (Default value is: c)
--print_kernel_info Print solution, kernel name and solution index.
--rotating <value> Use rotating memory blocks for each iteration, size in MB. (Default value is: 0)
--use_gpu_timer Use hipEventElapsedTime to profile elapsed time. (Default value is: false)
--splitk <value> [Tuning parameter] Set split K for a solution, 0 is use solution's default value. (Only support GEMM + api_method mix or cpp)
--wgm <value> [Tuning parameter] Set workgroup mapping for a solution, 0 is use solution's default value. (Only support GEMM + api_method mix or cpp)
--flush Flush icache
--help |-h produces this help message
--version <value> Prints the version number
Run fp32 GEMM with validation
./clients/staging/hipblaslt-bench --precision f32_r -v
transA,transB,M,N,K,alpha,lda,stride_a,beta,ldb,stride_b,ldc,stride_c,ldd,stride_d,d_type,compute_type,activation_type,bias_vector,hipblaslt-Gflops,us
N,N,128,128,128,1,128,16384,0,128,16384,128,16384,128,16384,f32_r,f32_r,none,0, 415.278, 10.1