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Diffstat (limited to 'configs/tested-cfgs/SM86_RTX3070/gpgpusim.config')
| -rw-r--r-- | configs/tested-cfgs/SM86_RTX3070/gpgpusim.config | 192 |
1 files changed, 192 insertions, 0 deletions
diff --git a/configs/tested-cfgs/SM86_RTX3070/gpgpusim.config b/configs/tested-cfgs/SM86_RTX3070/gpgpusim.config new file mode 100644 index 0000000..2010aa6 --- /dev/null +++ b/configs/tested-cfgs/SM86_RTX3070/gpgpusim.config @@ -0,0 +1,192 @@ +# This config models the Ampere RTX 3070 +# For more info about Ampere architecture: +# https://developer.download.nvidia.com/video/gputechconf/gtc/2020/presentations/s21730-inside-the-nvidia-ampere-architecture.pdf +# https://www.nvidia.com/content/dam/en-zz/Solutions/geforce/ampere/pdf/NVIDIA-ampere-GA102-GPU-Architecture-Whitepaper-V1.pdf +# https://en.wikipedia.org/wiki/GeForce_30_series +# functional simulator specification +-gpgpu_ptx_instruction_classification 0 +-gpgpu_ptx_sim_mode 0 +-gpgpu_ptx_force_max_capability 86 + +# Device Limits +-gpgpu_stack_size_limit 1024 +-gpgpu_heap_size_limit 8388608 +-gpgpu_runtime_sync_depth_limit 2 +-gpgpu_runtime_pending_launch_count_limit 2048 +-gpgpu_kernel_launch_latency 5000 +-gpgpu_TB_launch_latency 0 + +# Compute Capability +-gpgpu_compute_capability_major 8 +-gpgpu_compute_capability_minor 6 + +# PTX execution-driven +-gpgpu_ptx_convert_to_ptxplus 0 +-gpgpu_ptx_save_converted_ptxplus 0 + +# high level architecture configuration +-gpgpu_n_clusters 46 +-gpgpu_n_cores_per_cluster 1 +-gpgpu_n_mem 16 +-gpgpu_n_sub_partition_per_mchannel 2 + +# Ampere clock domains +#-gpgpu_clock_domains <Core Clock>:<Interconnect Clock>:<L2 Clock>:<DRAM Clock> +-gpgpu_clock_domains 1320.0:1320.0:1320.0:3500.0 +# boost mode +# -gpgpu_clock_domains 1780.0:1780.0:1780.0:3500.0 + +# shader core pipeline config +-gpgpu_shader_registers 65536 +-gpgpu_registers_per_block 65536 +-gpgpu_occupancy_sm_number 86 + +# This implies a maximum of 64 warps/SM +-gpgpu_shader_core_pipeline 2048:32 +-gpgpu_shader_cta 32 +-gpgpu_simd_model 1 + +# Pipeline widths and number of FUs +# ID_OC_SP,ID_OC_DP,ID_OC_INT,ID_OC_SFU,ID_OC_MEM,OC_EX_SP,OC_EX_DP,OC_EX_INT,OC_EX_SFU,OC_EX_MEM,EX_WB,ID_OC_TENSOR_CORE,OC_EX_TENSOR_CORE +## Ampere GA102 has 4 SP SIMD units, 4 SFU units, 4 DP units per core, 4 Tensor core units +## we need to scale the number of pipeline registers to be equal to the number of SP units +-gpgpu_pipeline_widths 4,4,4,4,4,4,4,4,4,4,8,4,4 +-gpgpu_num_sp_units 4 +-gpgpu_num_sfu_units 4 +-gpgpu_num_dp_units 4 +-gpgpu_num_int_units 4 +-gpgpu_tensor_core_avail 1 +-gpgpu_num_tensor_core_units 4 + +# Instruction latencies and initiation intervals +# "ADD,MAX,MUL,MAD,DIV" +# All Div operations are executed on SFU unit +-ptx_opcode_latency_int 4,13,4,5,145,21 +-ptx_opcode_initiation_int 2,2,2,2,8,4 +-ptx_opcode_latency_fp 4,13,4,5,39 +-ptx_opcode_initiation_fp 2,2,2,2,4 +-ptx_opcode_latency_dp 8,19,8,8,330 +-ptx_opcode_initiation_dp 4,4,4,4,130 +-ptx_opcode_latency_sfu 100 +-ptx_opcode_initiation_sfu 8 +-ptx_opcode_latency_tesnor 32 +-ptx_opcode_initiation_tensor 32 + +# Ampere has sub core model, in which each scheduler has its own register file and EUs +# i.e. schedulers are isolated +-gpgpu_sub_core_model 1 +# disable specialized operand collectors and use generic operand collectors instead +-gpgpu_enable_specialized_operand_collector 0 +-gpgpu_operand_collector_num_units_gen 8 +-gpgpu_operand_collector_num_in_ports_gen 8 +-gpgpu_operand_collector_num_out_ports_gen 8 +# Ampere has 24 double-ported banks, 4 schedulers, 6 banks per scheduler +-gpgpu_num_reg_banks 24 +-gpgpu_reg_file_port_throughput 2 + +# shared memory bankconflict detection +-gpgpu_shmem_num_banks 32 +-gpgpu_shmem_limited_broadcast 0 +-gpgpu_shmem_warp_parts 1 +-gpgpu_coalesce_arch 86 + +# Ampere has four schedulers per core +-gpgpu_num_sched_per_core 4 +# Greedy then oldest scheduler +-gpgpu_scheduler gto +## In Ampere, a warp scheduler can issue 1 inst per cycle +-gpgpu_max_insn_issue_per_warp 1 +-gpgpu_dual_issue_diff_exec_units 1 + +## L1/shared memory configuration +# <nsets>:<bsize>:<assoc>,<rep>:<wr>:<alloc>:<wr_alloc>:<set_index_fn>,<mshr>:<N>:<merge>,<mq>:**<fifo_entry> +# ** Optional parameter - Required when mshr_type==Texture Fifo +# Default config is 28KB DL1 and 100KB shared memory +# In Ampere, we assign the remaining shared memory to L1 cache +# if the assigned shd mem = 0, then L1 cache = 128KB +# For more info, see https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#global-memory-8-x +# disable this mode in case of multi kernels/apps execution +-gpgpu_adaptive_cache_config 1 +# Ampere unified cache has four banks +-gpgpu_l1_banks 4 +-gpgpu_cache:dl1 S:1:128:256,L:L:s:N:L,A:256:8,16:0,32 +-gpgpu_shmem_size 102400 +-gpgpu_shmem_sizeDefault 102400 +-gpgpu_shmem_per_block 102400 +-gpgpu_gmem_skip_L1D 0 +-gpgpu_n_cluster_ejection_buffer_size 32 +-gpgpu_l1_latency 20 +-gpgpu_smem_latency 20 +-gpgpu_flush_l1_cache 1 + +# 32 sets, each 128 bytes 24-way for each memory sub partition (96 KB per memory sub partition). This gives us 3MB L2 cache +-gpgpu_cache:dl2 S:32:128:24,L:B:m:L:P,A:192:4,32:0,32 +-gpgpu_cache:dl2_texture_only 0 +-gpgpu_dram_partition_queues 64:64:64:64 +-gpgpu_perf_sim_memcpy 1 +-gpgpu_memory_partition_indexing 2 + +# 128 KB Inst. +-gpgpu_cache:il1 N:64:128:16,L:R:f:N:L,S:2:48,4 +-gpgpu_inst_fetch_throughput 4 +# 128 KB Tex +# Note, TEX is deprecated, It is used for legacy apps only. Use L1D cache instead with .nc modifier or __ldg mehtod +-gpgpu_tex_cache:l1 N:4:128:256,L:R:m:N:L,T:512:8,128:2 +# 64 KB Const +-gpgpu_const_cache:l1 N:128:64:8,L:R:f:N:L,S:2:64,4 +-gpgpu_perfect_inst_const_cache 1 + +# interconnection +#-network_mode 1 +#-inter_config_file config_ampere_islip.icnt +# use built-in local xbar +-network_mode 2 +-icnt_in_buffer_limit 512 +-icnt_out_buffer_limit 512 +-icnt_subnets 2 +-icnt_flit_size 40 +-icnt_arbiter_algo 1 + +# memory partition latency config +-gpgpu_l2_rop_latency 160 +-dram_latency 100 + +# dram model config +-gpgpu_dram_scheduler 1 +-gpgpu_frfcfs_dram_sched_queue_size 64 +-gpgpu_dram_return_queue_size 192 + +# Ampere RTX3060 has GDDR6 +# http://monitorinsider.com/GDDR6.html +-gpgpu_n_mem_per_ctrlr 1 +-gpgpu_dram_buswidth 2 +-gpgpu_dram_burst_length 16 +-dram_data_command_freq_ratio 4 +-gpgpu_mem_address_mask 1 +-gpgpu_mem_addr_mapping dramid@8;00000000.00000000.00000000.00000000.0000RRRR.RRRRRRRR.RBBBCCCC.BCCSSSSS + +# Use the same GDDR5 timing, scaled to 3500MHZ +-gpgpu_dram_timing_opt "nbk=16:CCD=4:RRD=10:RCD=20:RAS=50:RP=20:RC=62: + CL=20:WL=8:CDLR=9:WR=20:nbkgrp=4:CCDL=4:RTPL=4" + +# select lower bits for bnkgrp to increase bnkgrp parallelism +-dram_bnk_indexing_policy 0 +-dram_bnkgrp_indexing_policy 1 + +#-dram_seperate_write_queue_enable 1 +#-dram_write_queue_size 64:56:32 + +# stat collection +-gpgpu_memlatency_stat 14 +-gpgpu_runtime_stat 500 +-enable_ptx_file_line_stats 1 +-visualizer_enabled 0 + +# power model configs, disable it untill we create a real energy model for Ampere +-power_simulation_enabled 0 + +# tracing functionality +#-trace_enabled 1 +#-trace_components WARP_SCHEDULER,SCOREBOARD +#-trace_sampling_core 0 + |
