Simulation Output Files - Scala Computing

The Scala NS3 network simulator produces CSV output files during each simulation run. These files capture detailed metrics about MPI communication, network device behavior, switch buffer utilization, application performance, and more. Each file type is identified by a naming pattern embedded in its filename. All output files are stored in S3 and can be accessed through the results API after a simulation completes.

How to Access Output Files

Use the simulation results endpoints to list and download output files: List result files:

curl -X GET "https://api.scalacomputing.com/api/v1/simulations/{sim_id}/results" \
  -H "Authorization: Bearer $SCALA_API_TOKEN"

Download a specific file via presigned URL:

curl -X GET "https://api.scalacomputing.com/api/v1/simulations/{sim_id}/results/download-url?fileName={file_name}" \
  -H "Authorization: Bearer $SCALA_API_TOKEN"

Retrieve computed summary statistics (nd-stats, perf, pfc only):

curl -X GET "https://api.scalacomputing.com/api/v1/simulations/{sim_id}/results/data?metric=nd-stats&tier=all" \
  -H "Authorization: Bearer $SCALA_API_TOKEN"

See the Simulations API Reference for full endpoint documentation.

File Naming Convention

Output files follow the pattern:

{simulation-name}-{file-type}-{shard-index}.csv

For example, a simulation named my-sim-2026-03-17 produces files like:

my-sim-2026-03-17-mpi-stats-0.csv
my-sim-2026-03-17-nd-stats-0.csv
my-sim-2026-03-17-nd-stats-1.csv

The shard index (-0, -1, …) allows the simulator to split large output across multiple files.

File Types Overview

File Type	Name Pattern	Description
MPI Statistics	`-mpi-stats-.csv`	MPI packet and transaction counters per time step
MPI Profiling	`-mpi-profiling-.csv`	Per-core MPI engine profiling counters and timing
Remote Trace Log	`-scala-remote-trace-log-.csv`	Trace-level log of remote MPI operations
Network Device Statistics	`-nd-stats-.csv`	Per-interface packet/byte counters, throughput, utilization
Performance Metrics	`-perf-.csv`	Application-level latency and transfer measurements
ECN/PFC Statistics	`-ecn-pfc-stats-.csv`	Priority Flow Control and ECN marking counters
Application Report	`-application-report-.csv`	Socket and application binding information
Beacon	`-beacon-.csv`	Periodic heartbeat counters for client/server traffic
CPU/Memory Statistics	`-cpu-mem-stats-.csv`	Host-level CPU and memory utilization of the simulator process
RoCE Transport Statistics	`-roce-transport-stats-.csv`	RDMA over Converged Ethernet transport-layer counters
Tier Hop	`-tier-hop-.csv`	Packet counts traversing each network tier
Topology Report	`-topology-report-.csv`	Static topology describing device interconnections
Switch Buffer Statistics	`-scala-switch-agg-buff-stats-.csv`	Aggregated switch buffer occupancy and utilization

Detailed File Schemas

MPI Statistics (mpi-stats)

MPI Statistics files record per-time-step counters for MPI packet and transaction activity across the simulated cluster. Use this file to analyze MPI communication volume over time. Filename pattern: {simulation}-mpi-stats-{shard}.csv

Columns

Column	Type	Description
`job_id`	String	Identifier for the simulation job
`time_utc`	String (ISO 8601)	Wall-clock timestamp when the row was emitted
`sim_time_sec`	Float	Simulated time in seconds
`mpi_pkt_tx`	Integer	Cumulative MPI packets transmitted
`mpi_pkt_rx`	Integer	Cumulative MPI packets received
`mpi_tr_tx`	Integer	Cumulative MPI transactions (operations) transmitted
`mpi_tr_rx`	Integer	Cumulative MPI transactions (operations) received
`mpi_app_tag_tx`	Integer	Cumulative MPI application-tagged messages transmitted
`mpi_app_tag_rx`	Integer	Cumulative MPI application-tagged messages received
`mpi_null`	Integer	Count of MPI null/idle events

Example Row

job_id,time_utc,sim_time_sec,mpi_pkt_tx,mpi_pkt_rx,mpi_tr_tx,mpi_tr_rx,mpi_app_tag_tx,mpi_app_tag_rx,mpi_null
example,2026-01-13T19:11:39Z,0.003,0,0,0,0,0,0,0

MPI Profiling (mpi-profiling)

MPI Profiling files capture per-core performance counters and timing breakdowns for the MPI simulation engine. Each row represents one core’s profiling snapshot at a given simulation time step. Use this file to identify bottlenecks in the parallel simulation engine. Filename pattern: {simulation}-mpi-profiling-{shard}.csv

Columns

Column	Type	Description
`job_id`	String	Identifier for the simulation job
`time_utc`	String (ISO 8601)	Wall-clock timestamp when the row was emitted
`sim_time_sec`	Float	Simulated time in seconds
`core`	Integer	Core/rank index within the MPI engine
`cntWhile`	Integer	Number of main-loop iterations
`cntCalcGrantedTime`	Integer	Count of granted-time calculations
`cntWhileNextGreater`	Integer	Iterations where next event time exceeded current window
`cntWhileIsLocalFinished`	Integer	Iterations where the local partition finished early
`cntWhileBoth`	Integer	Iterations matching both NextGreater and IsLocalFinished
`cntRxEqTx`	Integer	Iterations where receive count equaled transmit count
`cntRxEqTxLookAheadEqMax`	Integer	RxEqTx iterations where lookahead equaled max
`cntRxEqTxLookAheadNeqMax`	Integer	RxEqTx iterations where lookahead did not equal max
`cntRxNeqTx`	Integer	Iterations where receive count did not equal transmit count
`num_processed_events`	Integer	Cumulative number of discrete events processed
`testTime_sec`	Float	Wall-clock time spent in the test phase (seconds)
`mtestTime_sec`	Float	Wall-clock time for the MPI test phase (seconds)
`timeReceive_sec`	Float	Wall-clock time spent in MPI receive calls (seconds)
`mtimeReceive_sec`	Float	Wall-clock time for MPI-level receive (seconds)
`timeSend_sec`	Float	Wall-clock time spent in MPI send calls (seconds)
`mtimeSend_sec`	Float	Wall-clock time for MPI-level send (seconds)
`timeGather_sec`	Float	Wall-clock time spent in MPI gather calls (seconds)
`mtimeGather_sec`	Float	Wall-clock time for MPI-level gather (seconds)
`timeEvents_sec`	Float	Wall-clock time spent processing events (seconds)
`mtimeEvents_sec`	Float	Wall-clock time for MPI-level event processing (seconds)

Example Row

job_id,time_utc,sim_time_sec,core,cntWhile,cntCalcGrantedTime,cntWhileNextGreater,cntWhileIsLocalFinished,cntWhileBoth,cntRxEqTx,cntRxEqTxLookAheadEqMax,cntRxEqTxLookAheadNeqMax,cntRxNeqTx,num_processed_events,testTime_sec,mtestTime_sec,timeReceive_sec,mtimeReceive_sec,timeSend_sec,mtimeSend_sec,timeGather_sec,mtimeGather_sec,timeEvents_sec,mtimeEvents_sec
example,2026-01-13T19:11:39Z,0.003,0,1498198,0,0,0,0,0,0,0,0,1498198,5.84884437,9.62542344,0,0,0,0,0,0,0,0

Remote Trace Log (scala-remote-trace-log)

Remote Trace Log files record individual remote MPI operations at trace level, capturing the source and destination ranks, buffer contents, and channel timing for each remote call. This file is useful for debugging specific MPI communication patterns and diagnosing latency in remote operations. Filename pattern: {simulation}-scala-remote-trace-log-{shard}.csv

Columns

Column	Type	Description
`time_utc`	String (ISO 8601)	Wall-clock timestamp when the event was logged
`sim_time`	Float	Simulated time at which the remote operation occurred
`source`	String	Source identifier for the trace event
`remote_trace_client_id`	String	Unique identifier for the remote trace client
`src_rank`	Integer	Source MPI rank initiating the operation
`dest_rank`	Integer	Destination MPI rank receiving the operation
`string_buf`	String	String representation of the buffer contents
`buf_size`	Integer	Size of the buffer in bytes
`status`	String	Status of the remote operation
`channel_delay`	Float	Channel delay for the remote operation (units vary by configuration)

Note: This file may be empty if no remote MPI trace events occurred during the simulation.

Example Header

time_utc,sim_time,source,remote_trace_client_id,src_rank,dest_rank,string_buf,buf_size,status,channel_delay

Network Device Statistics (nd-stats)

Network Device Statistics files contain per-interface, per-time-step counters for every network device in the simulated topology. Each row captures packet counts, byte volumes, throughput rates, link utilization percentages, and drop counters. This is one of the three metric types that supports server-side summary aggregation via the results data endpoint. Filename pattern: {simulation}-nd-stats-{shard}.csv

Columns

Column	Type	Description
`time_utc`	String	Wall-clock timestamp (ISO 8601)
`sim_time_sec`	Float64	Simulated time in seconds
`component_name`	String	Name of the network component (e.g., `ScalaFabricSwitch-0-0-0-0-1-0`)
`nd_name`	String	Network device class name
`component_type`	String	Type of component (e.g., `Switch`)
`ifid`	Int64	Interface ID on the device
`uldl`	String	Direction: `ul` (uplink) or `dl` (downlink)
`node_id`	Int64	Unique node identifier
`tier`	Int32	Network tier (0=Spine, 1=Fabric, 2=Rack, 3=NIC)
`subtier`	Int64	Sub-tier identifier
`total_packets_tx`	Int64	Cumulative packets transmitted
`total_packets_rx`	Int64	Cumulative packets received
`total_bytes_tx_GB`	Float64	Cumulative bytes transmitted (GB)
`total_bytes_rx_GB`	Float64	Cumulative bytes received (GB)
`interval_bytes_tx_MB`	Float64	Bytes transmitted in the current interval (MB)
`interval_bytes_rx_MB`	Float64	Bytes received in the current interval (MB)
`tx_rate_Gbps`	Float64	Transmit rate (Gbps)
`rx_rate_Gbps`	Float64	Receive rate (Gbps)
`tx_link_percent_util`	Float64	Transmit link utilization (percent)
`rx_link_percent_util`	Float64	Receive link utilization (percent)
`tx_drops`	Int64	Cumulative transmit-side drops
`rx_drops`	Int64	Cumulative receive-side drops

Network Tiers

Tier Value	Abbreviation	Description
0	SSW	Spine Switch
1	FSW	Fabric Switch
2	RSW	Rack Switch
3	NIC	Network Interface Card

Example Row

time_utc,sim_time_sec,component_name,nd_name,component_type,ifid,uldl,node_id,tier,subtier,total_packets_tx,total_packets_rx,total_bytes_tx_GB,total_bytes_rx_GB,interval_bytes_tx_MB,interval_bytes_rx_MB,tx_rate_Gbps,rx_rate_Gbps,tx_link_percent_util,rx_link_percent_util,tx_drops,rx_drops
2026-01-13T19:11:38Z,0.003,ScalaFabricSwitch-0-0-0-0-1-0,scala_switch::ScalaSwitchEthNetDevice,Switch,0,dl,0,1,4294967295,115,112,7.3062e-05,7.4146e-05,0.073062,0.074146,0.584496,0.593168,0.073062,0.074146,0,0

Performance Metrics (perf)

Performance Metrics files capture application-level latency and transfer size measurements for each completed transaction. Each row represents one transaction observed by a traffic generator. This is one of the three metric types that supports server-side summary aggregation. Filename pattern: {simulation}-perf-{shard}.csv

Columns

Column	Type	Description
`job_id`	String	Identifier for the simulation job
`time_utc`	String	Wall-clock timestamp (ISO 8601)
`sim_time_sec`	Float64	Simulated time in seconds
`metric_name`	String	Name of the performance metric (e.g., `ScalaApp`)
`perf_metric_usec`	Float64	Measured latency in microseconds
`metric_path`	String	Hierarchical path for the metric
`metric_aggregation_id`	String	Aggregation group identifier
`node_id`	Int64	Node that recorded the metric
`transaction_number`	Int64	Sequential transaction number
`start_time_sec`	Float64	Simulation time when the transaction started (seconds)
`transfer_size_b`	Float64	Transfer size in bytes
`application_name`	String	Name of the application that generated the transaction

Example Row

job_id,time_utc,sim_time_sec,metric_name,perf_metric_usec,metric_path,metric_aggregation_id,node_id,transaction_number,start_time_sec,transfer_size_b,application_name
example,2026-01-13T19:11:40Z,0.00500019,ScalaApp,2.83117,NAN,NAN,478,4,0.00499736,NAN,TrafficGeneratorClient-P:0-R:3-S:24-R:0-C:0-1554

ECN/PFC Statistics (ecn-pfc-stats)

ECN/PFC Statistics files record Priority Flow Control (PFC) frame counters and Explicit Congestion Notification (ECN) marking counts per interface, per priority level. Use this data to analyze congestion events and flow control behavior. This is one of the three metric types that supports server-side summary aggregation. Filename pattern: {simulation}-ecn-pfc-stats-{shard}.csv

Columns

Column	Type	Description
`job_id`	String	Identifier for the simulation job
`time_utc`	String	Wall-clock timestamp (ISO 8601)
`sim_time_sec`	Float64	Simulated time in seconds
`node_id`	Int64	Unique node identifier
`component_name`	String	Name of the network component
`component_type`	String	Type of component (e.g., `Switch`)
`ifid`	Int64	Interface ID
`uldl`	String	Direction: `ul` (uplink) or `dl` (downlink)
`tier`	Int32	Network tier (0=Spine, 1=Fabric, 2=Rack, 3=NIC)
`subtier`	Int64	Sub-tier identifier
`priority`	Int64	Traffic priority class
`pfcxoff_tx`	Int64	PFC XOFF frames transmitted
`pfcxoff_rx`	Int64	PFC XOFF frames received
`pfcxon_tx`	Int64	PFC XON frames transmitted
`pfcxon_rx`	Int64	PFC XON frames received
`pfc_time_paused_usec`	Float64	Cumulative time paused due to PFC (microseconds)
`interval_total_time_xoff_usec`	Float64	Total XOFF time in the current interval (microseconds)
`interval_max_time_xoff_usec`	Float64	Maximum single XOFF duration in the interval (microseconds)
`interval_total_time_xoff_egr_occ_usec`	Float64	Total XOFF time due to egress occupancy in the interval (microseconds)
`interval_max_time_xoff_egr_occ_usec`	Float64	Maximum single XOFF duration due to egress occupancy (microseconds)
`total_xoff_time_egr_occ_usec`	Float64	Cumulative XOFF time due to egress occupancy (microseconds)
`percent_xon`	Float64	Percentage of time the interface was in XON state
`xoff_egr_occ_ratio`	Float64	Ratio of XOFF time attributed to egress occupancy
`pkts_ecn_marked`	Int64	Number of packets marked with ECN

Note: The microsecond-duration columns are fractional (Float64); the simulator derives them from nanosecond timers divided by 1000. Server-side PFC summary values (e.g. totalTimePausedUsec) may therefore be non-integer.

Example Header

job_id,time_utc,sim_time_sec,node_id,component_name,component_type,ifid,uldl,tier,subtier,priority,pfcxoff_tx,pfcxoff_rx,pfcxon_tx,pfcxon_rx,pfc_time_paused_usec,interval_total_time_xoff_usec,interval_max_time_xoff_usec,interval_total_time_xoff_egr_occ_usec,interval_max_time_xoff_egr_occ_usec,total_xoff_time_egr_occ_usec,percent_xon,xoff_egr_occ_ratio,pkts_ecn_marked

Application Report (application-report)

Application Report files describe the socket bindings established at simulation startup. Each row maps a host component and node to its application type, socket role, DSCP/ECT settings, and peer node. Filename pattern: {simulation}-application-report-{shard}.csv

Columns

Column	Type	Description
`job_id`	String	Identifier for the simulation job
`time_utc`	String (ISO 8601)	Wall-clock timestamp
`component_name`	String	Host component name (e.g., `ScalaHost-0-0-0-0`)
`node_id`	Integer	Unique node identifier
`socket_type`	String	Socket role: `CLIENT` or `SERVER`
`app_typeid`	String	NS3 application type (e.g., `ns3::ScalaTrafficGeneratorApplication`)
`app_name`	String	Application instance name
`dscp`	Integer	Differentiated Services Code Point value
`ect`	Integer	ECN-Capable Transport flag
`peer_node_id`	Integer	Node ID of the communication peer

Example Row

job_id,time_utc,component_name,node_id,socket_type,app_typeid,app_name,dscp,ect,peer_node_id
example,2026-01-13T19:11:37Z,ScalaHost-0-0-0-0,262,CLIENT,ns3::ScalaTrafficGeneratorApplication,TrafficGeneratorClient-P:0-R:0-S:0-R:0-C:0-1,0,0,386

Beacon (beacon)

Beacon files record periodic heartbeat counters tracking client and server packet activity and data goodput over each reporting interval. Filename pattern: {simulation}-beacon-{shard}.csv

Columns

Column	Type	Description
`job_id`	String	Identifier for the simulation job
`time_utc`	String (ISO 8601)	Wall-clock timestamp
`sim_time_sec`	Float	Simulated time in seconds
`interval_duration_sec`	Float	Duration of the reporting interval (seconds)
`tx_client`	Integer	Cumulative packets transmitted by clients
`rx_client`	Integer	Cumulative packets received by clients
`tx_server`	Integer	Cumulative packets transmitted by servers
`rx_server`	Integer	Cumulative packets received by servers
`rx_bytes_reader`	Integer	Cumulative bytes received by reader applications
`rx_bytes_writer`	Integer	Cumulative bytes received by writer applications
`goodput_reader_MB_per_sec`	Float	Reader goodput for the interval (MB/s)
`goodput_writer_MB_per_sec`	Float	Writer goodput for the interval (MB/s)

Example Row

job_id,time_utc,sim_time_sec,interval_duration_sec,tx_client,rx_client,tx_server,rx_server,rx_bytes_reader,rx_bytes_writer,goodput_reader_MB_per_sec,goodput_writer_MB_per_sec
example,2026-01-13T19:11:42Z,0.006,1,5027,5027,5027,5027,0,1314708,0,52.5883

CPU/Memory Statistics (cpu-mem-stats)

CPU/Memory Statistics files capture host-level resource utilization of the simulator process itself, including virtual memory, RSS, system memory, swap, and CPU time breakdowns. Filename pattern: {simulation}-cpu-mem-stats-{shard}.csv

Columns

Column	Type	Description
`job_id`	String	Identifier for the simulation job
`time_utc`	String (ISO 8601)	Wall-clock timestamp
`sim_time_sec`	Float	Simulated time in seconds
`host_name`	String	Hostname of the machine running the simulator
`pid`	Integer	Process ID of the simulator
`core_vm_usage_M`	Float	Virtual memory used by the process (MB)
`core_rss_M`	Float	Resident set size of the process (MB)
`core_vm_usage_pct`	Float	Virtual memory usage as a percentage of system total
`core_rss_usage_pct`	Float	RSS usage as a percentage of system total
`sys_total_mem_M`	Float	Total system memory (MB)
`sys_free_mem_M`	Float	Free system memory (MB)
`sys_used_mem_M`	Float	Used system memory (MB)
`sys_mem_usage_pct`	Float	System memory usage percentage
`sys_swap_usage_pct`	Float	System swap usage percentage
`user_time_ticks`	Integer	CPU time in user mode (ticks)
`kernel_time_ticks`	Integer	CPU time in kernel mode (ticks)
`total_time_ticks`	Integer	Total CPU time (ticks)
`elapse_time_ticks`	Integer	Elapsed wall-clock time (ticks)
`user_time_pct`	Float	User CPU time as a percentage
`system_time_pct`	Float	System/kernel CPU time as a percentage
`total_time_pct`	Float	Total CPU time as a percentage

Example Header

job_id,time_utc,sim_time_sec,host_name,pid,core_vm_usage_M,core_rss_M,core_vm_usage_pct,core_rss_usage_pct,sys_total_mem_M,sys_free_mem_M,sys_used_mem_M,sys_mem_usage_pct,sys_swap_usage_pct,user_time_ticks,kernel_time_ticks,total_time_ticks,elapse_time_ticks,user_time_pct,system_time_pct,total_time_pct

RoCE Transport Statistics (roce-transport-stats)

RoCE Transport Statistics files record detailed RDMA over Converged Ethernet (RoCEv2) transport-layer counters per network device. This includes packet counts by verb type, acknowledgment/NACK tracking, reordering buffer statistics, work queue entries, retransmissions, and round-trip time measurements. Filename pattern: {simulation}-roce-transport-stats-{shard}.csv

Columns

Column	Type	Description
`time_utc`	String (ISO 8601)	Wall-clock timestamp
`sim_time_sec`	Float	Simulated time in seconds
`component_name`	String	Host component name
`node_id`	Integer	Unique node identifier
`num_pkts_sent`	Integer	Cumulative packets sent
`ivl_num_pkts_sent`	Integer	Packets sent in the current interval
`num_verb_pkts_sent`	Integer	Cumulative verb (data) packets sent
`ivl_num_verb_pkts_sent`	Integer	Verb packets sent in the interval
`num_non_verb_pkts_sent`	Integer	Cumulative non-verb (control) packets sent
`ivl_num_non_verb_pkts_sent`	Integer	Non-verb packets sent in the interval
`num_conn_pkts_sent`	Integer	Cumulative connection packets sent
`ivl_num_conn_pkts_sent`	Integer	Connection packets sent in the interval
`num_conn_pkts_recvd`	Integer	Cumulative connection packets received
`ivl_num_conn_pkts_recvd`	Integer	Connection packets received in the interval
`rdma_write_cnt`	Integer	Cumulative RDMA WRITE operations
`ivl_rdma_write_cnt`	Integer	RDMA WRITE operations in the interval
`rdma_send_cnt`	Integer	Cumulative RDMA SEND operations
`ivl_rdma_send_cnt`	Integer	RDMA SEND operations in the interval
`rdma_atomic_cnt`	Integer	Cumulative RDMA ATOMIC operations
`ivl_rdma_atomic_cnt`	Integer	RDMA ATOMIC operations in the interval
`num_acks_sent`	Integer	Cumulative ACKs sent
`ivl_num_acks_sent`	Integer	ACKs sent in the interval
`num_acks_recvd`	Integer	Cumulative ACKs received
`ivl_num_acks_recvd`	Integer	ACKs received in the interval
`num_sacks_sent`	Integer	Cumulative selective ACKs sent
`ivl_num_sacks_sent`	Integer	Selective ACKs sent in the interval
`num_sacks_recvd`	Integer	Cumulative selective ACKs received
`ivl_num_sacks_recvd`	Integer	Selective ACKs received in the interval
`num_nacks_sent`	Integer	Cumulative NACKs sent
`ivl_num_nacks_sent`	Integer	NACKs sent in the interval
`num_nacks_recvd`	Integer	Cumulative NACKs received
`ivl_num_nacks_recvd`	Integer	NACKs received in the interval
`num_writes_recvd`	Integer	Cumulative RDMA WRITE operations received
`ivl_num_writes_recvd`	Integer	RDMA WRITE operations received in the interval
`num_sends_recvd`	Integer	Cumulative RDMA SEND operations received
`ivl_num_sends_recvd`	Integer	RDMA SEND operations received in the interval
`num_cnp_sent`	Integer	Cumulative Congestion Notification Packets sent
`ivl_num_cnp_sent`	Integer	CNPs sent in the interval
`num_cnp_recvd`	Integer	Cumulative CNPs received
`ivl_num_cnp_recvd`	Integer	CNPs received in the interval
`num_seq_out_of_order`	Integer	Cumulative out-of-order sequence events
`ivl_num_seq_out_of_order`	Integer	Out-of-order events in the interval
`ivl_min_size_reorder_buf_psn`	Integer	Minimum reorder buffer size in the interval (PSN entries)
`max_size_reorder_buf_psn`	Integer	Maximum reorder buffer size observed (PSN entries)
`ivl_max_size_reorder_buf_psn`	Integer	Maximum reorder buffer size in the interval
`avg_size_reorder_buf_psn`	Float	Average reorder buffer size (PSN entries)
`ivl_avg_size_reorder_buf_psn`	Float	Average reorder buffer size in the interval
`num_wqe_created`	Integer	Cumulative Work Queue Entries created
`ivl_num_wqe_created`	Integer	WQEs created in the interval
`num_wqe_completed`	Integer	Cumulative WQEs completed
`ivl_num_wqe_completed`	Integer	WQEs completed in the interval
`num_rtx`	Integer	Cumulative retransmissions
`ivl_num_rtx`	Integer	Retransmissions in the interval
`num_rto`	Integer	Cumulative retransmission timeouts
`ivl_num_rto`	Integer	RTOs in the interval
`ivl_min_calc_rtt_usec`	Float	Minimum calculated RTT in the interval (microseconds)
`max_calc_rtt_usec`	Float	Maximum calculated RTT observed (microseconds)
`ivl_max_calc_rtt_usec`	Float	Maximum calculated RTT in the interval (microseconds)
`avg_calc_rtt_usec`	Float	Average calculated RTT (microseconds)
`ivl_avg_calc_rtt_usec`	Float	Average calculated RTT in the interval (microseconds)

Example Header

time_utc,sim_time_sec,component_name,node_id,num_pkts_sent,ivl_num_pkts_sent,num_verb_pkts_sent,ivl_num_verb_pkts_sent,num_non_verb_pkts_sent,ivl_num_non_verb_pkts_sent,num_conn_pkts_sent,ivl_num_conn_pkts_sent,num_conn_pkts_recvd,ivl_num_conn_pkts_recvd,rdma_write_cnt,ivl_rdma_write_cnt,rdma_send_cnt,ivl_rdma_send_cnt,rdma_atomic_cnt,ivl_rdma_atomic_cnt,num_acks_sent,ivl_num_acks_sent,num_acks_recvd,ivl_num_acks_recvd,num_sacks_sent,ivl_num_sacks_sent,num_sacks_recvd,ivl_num_sacks_recvd,num_nacks_sent,ivl_num_nacks_sent,num_nacks_recvd,ivl_num_nacks_recvd,num_writes_recvd,ivl_num_writes_recvd,num_sends_recvd,ivl_num_sends_recvd,num_cnp_sent,ivl_num_cnp_sent,num_cnp_recvd,ivl_num_cnp_recvd,num_seq_out_of_order,ivl_num_seq_out_of_order,ivl_min_size_reorder_buf_psn,max_size_reorder_buf_psn,ivl_max_size_reorder_buf_psn,avg_size_reorder_buf_psn,ivl_avg_size_reorder_buf_psn,num_wqe_created,ivl_num_wqe_created,num_wqe_completed,ivl_num_wqe_completed,num_rtx,ivl_num_rtx,num_rto,ivl_num_rto,ivl_min_calc_rtt_usec,max_calc_rtt_usec,ivl_max_calc_rtt_usec,avg_calc_rtt_usec,ivl_avg_calc_rtt_usec

Tier Hop (tier-hop)

Tier Hop files record the cumulative and interval packet counts traversing each network tier (spine, fabric, rack). Use this to understand traffic distribution across the network hierarchy. Filename pattern: {simulation}-tier-hop-{shard}.csv

Columns

Column	Type	Description
`job_id`	String	Identifier for the simulation job
`time_utc`	String (ISO 8601)	Wall-clock timestamp
`sim_time_sec`	Float	Simulated time in seconds
`spine`	Integer	Cumulative packets through the spine tier
`fabric`	Integer	Cumulative packets through the fabric tier
`rack`	Integer	Cumulative packets through the rack tier
`spineInt`	Integer	Packets through the spine tier in the current interval
`fabricInt`	Integer	Packets through the fabric tier in the current interval
`rackInt`	Integer	Packets through the rack tier in the current interval

Example Row

job_id,time_utc,sim_time_sec,spine,fabric,rack,spineInt,fabricInt,rackInt
example,2026-01-13T19:11:39Z,0.003,0,18137,42672,0,18137,42672

Topology Report (topology-report)

Topology Report files describe the static physical topology of the simulated network. Each row represents one link between two devices, including tier placement, device type, link speed, and propagation delay. This file is emitted once per simulation and does not change over time. Filename pattern: {simulation}-topology-report-{shard}.csv

Columns

Column	Type	Description
`component_name`	String	Name of the source component
`component_type`	String	Type of source component (e.g., `Switch`)
`tier`	Integer	Network tier of the source component
`subtier`	Integer	Sub-tier of the source component
`node_id`	Integer	Node ID of the source component
`net_device`	String	Network device class on the source side
`dev_id`	Integer	Device/interface ID on the source side
`peer_component_name`	String	Name of the peer component
`peer_component_type`	String	Type of peer component
`peer_tier`	Integer	Network tier of the peer component
`peer_subtier`	Integer	Sub-tier of the peer component
`peer_node_id`	Integer	Node ID of the peer component
`peer_net_device`	String	Network device class on the peer side
`peer_dev_id`	Integer	Device/interface ID on the peer side
`linkspeed_Gbps`	Float	Link speed in Gbps
`prop_delay_ns`	Float	Propagation delay in nanoseconds

Example Row

component_name,component_type,tier,subtier,node_id,net_device,dev_id,peer_component_name,peer_component_type,peer_tier,peer_subtier,peer_node_id,peer_net_device,peer_dev_id,linkspeed_Gbps,prop_delay_ns
ScalaFabricSwitch-0-0-0-0-1-0,Switch,1,4294967295,0,scala_switch::ScalaSwitchEthNetDevice,0,ScalaRackSwitch-2-2-0-0-2-0,Switch,2,4294967295,2,scala_switch::ScalaSwitchEthNetDevice,0,800,500

Switch Buffer Statistics (scala-switch-agg-buff-stats)

Switch Buffer Statistics files capture aggregated buffer occupancy metrics for each switch in the network. Each row reports buffer utilization for a specific buffer type (egress queue, ingress usage, or shared buffer), direction, and pool on a given switch at a given time step. Filename pattern: {simulation}-scala-switch-agg-buff-stats-{shard}.csv

Columns

Column	Type	Description
`time_utc`	String (ISO 8601)	Wall-clock timestamp
`sim_time_sec`	Float	Simulated time in seconds
`component_name`	String	Switch component name
`tier`	Integer	Network tier of the switch
`node_id`	Integer	Unique node identifier
`buff_id`	String	Buffer type: `egressQueue`, `ingressUsage`, or `sharedBuffer`
`uldl`	String	Direction: `ul` (uplink), `dl` (downlink), or `-` (shared)
`pool_num`	Integer	Buffer pool number
`total_bytes`	Integer	Total bytes that have passed through the buffer
`buffer_limit`	Integer	Maximum buffer capacity in bytes
`ivl_count`	Integer	Number of samples in the interval
`ivl_min_bytes`	Integer	Minimum buffer occupancy in the interval (bytes)
`ivl_max_bytes`	Integer	Maximum buffer occupancy in the interval (bytes)
`ivl_mean_bytes`	Float	Mean buffer occupancy in the interval (bytes)
`ivl_max_pct_util`	Float	Maximum buffer utilization in the interval (fraction)
`ivl_mean_pct_util`	Float	Mean buffer utilization in the interval (fraction)

Example Row

time_utc,sim_time_sec,component_name,tier,node_id,buff_id,uldl,pool_num,total_bytes,buffer_limit,ivl_count,ivl_min_bytes,ivl_max_bytes,ivl_mean_bytes,ivl_max_pct_util,ivl_mean_pct_util
2026-01-13T19:11:39Z,0.003,ScalaFabricSwitch-0-0-0-0-1-0,1,0,egressQueue,dl,0,8856181,213308112,18114,0,5530,488.914,0.00259249,0.000229205

Per-Port Switch Buffer Statistics (scala-switch-buff-stats)

Per-Port Switch Buffer Statistics files carry the same measurements as the aggregate file above, but broken out per interface rather than summed across the switch. This is the only view of an individual queue’s occupancy against that queue’s own limit. Emitted only when the switch’s ReportPerPortBufferStats attribute is enabled; it is off by default, so most runs will not produce this file. Filename pattern: {simulation}-scala-switch-buff-stats-{shard}.csv

Columns

Column	Type	Description
`time_utc`	String (ISO 8601)	Wall-clock timestamp when the interval was reported
`sim_time_sec`	Float	Simulated time at the end of the reporting interval
`component_name`	String	Switch component name
`tier`	Integer	Network tier of the switch
`node_id`	Integer	Unique node identifier
`buff_id`	String	Buffer type: `egressQueue`, `ingressUsage`, or `hdrm`
`ifid`	Integer	Interface identifier — the port this row describes
`uldl`	String	Direction: `ul` (uplink) or `dl` (downlink)
`pool_num`	Integer	Buffer pool number
`buff_limit`	Integer	This port and pool’s own limit in bytes
`ivl_count`	Integer	Number of samples in the interval
`ivl_min_bytes`	Integer	Minimum occupancy in the interval (bytes)
`ivl_max_bytes`	Integer	Maximum occupancy in the interval (bytes)
`ivl_mean_bytes`	Float	Mean occupancy in the interval (bytes)
`ivl_max_pct_util`	Float	Maximum utilization in the interval, clamped at 100
`ivl_mean_pct_util`	Float	Mean utilization in the interval, clamped at 100

Note: Both percentage columns are clamped at 100, so an occupancy that exceeds its configured limit is not visible in them. Compute the ratio from ivl_max_bytes and buff_limit if you need the true figure.

Example Row

time_utc,sim_time_sec,component_name,tier,node_id,buff_id,ifid,uldl,pool_num,buff_limit,ivl_count,ivl_min_bytes,ivl_max_bytes,ivl_mean_bytes,ivl_max_pct_util,ivl_mean_pct_util
2026-08-18T20:09:09Z,0.001,Pod-1-0.Rack-1.ScalaSwitchRack-2-0-0,2,0,egressQueue,0,dl,0,40960000,43764,4136,127066192,7.37875e+07,100,100

​How to Access Output Files

​File Naming Convention

​File Types Overview

​Detailed File Schemas

​MPI Statistics (mpi-stats)

​Columns

​Example Row

​MPI Profiling (mpi-profiling)

​Columns

​Example Row

​Remote Trace Log (scala-remote-trace-log)

​Columns

​Example Header

​Network Device Statistics (nd-stats)

​Columns

​Network Tiers

​Example Row

​Performance Metrics (perf)

​Columns

​Example Row

​ECN/PFC Statistics (ecn-pfc-stats)

​Columns

​Example Header

​Application Report (application-report)

​Columns

​Example Row

​Beacon (beacon)

​Columns

​Example Row

​CPU/Memory Statistics (cpu-mem-stats)

​Columns

​Example Header

​RoCE Transport Statistics (roce-transport-stats)

​Columns

​Example Header

​Tier Hop (tier-hop)

​Columns

​Example Row

​Topology Report (topology-report)

​Columns

​Example Row

​Switch Buffer Statistics (scala-switch-agg-buff-stats)

​Columns

​Example Row

​Per-Port Switch Buffer Statistics (scala-switch-buff-stats)

​Columns

​Example Row

How to Access Output Files

File Naming Convention

File Types Overview

Detailed File Schemas

MPI Statistics (mpi-stats)

Columns

Example Row

MPI Profiling (mpi-profiling)

Columns

Example Row

Remote Trace Log (scala-remote-trace-log)

Columns

Example Header

Network Device Statistics (nd-stats)

Columns

Network Tiers

Example Row

Performance Metrics (perf)

Columns

Example Row

ECN/PFC Statistics (ecn-pfc-stats)

Columns

Example Header

Application Report (application-report)

Columns

Example Row

Beacon (beacon)

Columns

Example Row

CPU/Memory Statistics (cpu-mem-stats)

Columns

Example Header

RoCE Transport Statistics (roce-transport-stats)

Columns

Example Header

Tier Hop (tier-hop)

Columns

Example Row

Topology Report (topology-report)

Columns

Example Row

Switch Buffer Statistics (scala-switch-agg-buff-stats)

Columns

Example Row

Per-Port Switch Buffer Statistics (scala-switch-buff-stats)

Columns

Example Row