Hall D Online Data Acquisition CEBAF provides us with a tremendous scientific opportunity for understanding one of the fundamental forces of nature. 75 MB/s 900 MB/s

Critical Role for Computing in Hall D The quality of Hall D science depends critically upon the collaboration’s ability to conduct it’s computing tasks.

Design Focus Get the job done Minimize the effort required to perform computing Fewer physicists Lower development costs Lower hardware costs Keep it simple Provide for ubiquitous access and participation

Goals for the Computing Environment 1. Only two people are required to run the experiment. 2. Everyone can participate in solving experimental problems – no matter where they are located. 3. Offline analysis can more than keep up with the online acquisition. 4. Simulations can more than keep up with the online acquisition. 5. First pass analysis and simulations can be planned, conducted, monitored, validated and used by a group. 6. First pass analysis and simulations can conducted automatically with group monitoring. 7. Subsequent analysis can be done automatically if individuals so choose.

Goal #1: Two person acquisition team 100 MB/s raw data. Need an estimate of designed good event rate to set online trigger performance Automated system monitoring Automated slow controls Automated data acquisition Automated online farm Collaborative environment for access to experts Integrated problem solving database links current to past problems and solutions Well defined procedures Good training procedures

Goal #2: Ubiquitous expert participation Online system information available from the web. Collaborative environment for working with online team. Experts can control systems from elsewhere when data acquisition team allows or DAQ inactive.

Goal #3: Concurrent Offline Analysis Offline analysis can be completed in the same length of time as is required for data taking (including detector and accelerator down time). This includes: Calibration overhead. Multiple passes through the data (average of 2). Evaluation of results. Dissemination of results

Goal #4: Concurrent Simulations Simulations can be completed in the same length of time as is required for data taking (including detector and accelerator down time). This includes: Simulation planning. Systematic studies ( up to 5-10 times as much data as is required for experimental measurements). Analysis of simulation results. Dissemination of results.

Goal #5: Collaborative computing First pass analysis and simulations can be planned by a group. Multiple people can conduct, validate, monitor, evaluate and use first pass analysis and simulations without unnecessary duplication. A single individual or a large group can manage appropriate scale tasks effectively.

Goal #6: Automated computing First pass analysis and simulations can conducted automatically without intervention. Progress is reported automatically. Errors in automatic processing are automatically flagged.

Goal #7: Extensibility Subsequent analysis can be done automatically if individuals so choose. The computational management system can be extended to include any Hall D computing tasks.

April 16, 2001L. Dennis, FSU Technical Details Technical requirements that the computing system must meet.

Technical Details 100 MB/s raw data. Need an estimate of designed good event rate to set online trigger performance. Average of two analysis passes through the data. Average of 10 events simulated for every event taken. All required information available online – no electronically generated information will go unrecorded. All computer tasks automated - can be submitted and monitored from any computer system that can reach the internet.

Trigger Rates for Hall D Detector 180 kev/s Trigger 15 kev/s 5 kB/ev 75 MB/s Trigger requires ~100 CPU’s* * Assume a factor of 10 improvement over existing CPU’s 5 CPU-ms/evFull Reconstruction (CLAS) 50 ms/ev today. 100 CPU-ms/evFull Simulation (CLAS) 1-3 s/ev today. 1/3Assumed detector & accelerator efficiency.

Required Sustained Reconstruction Rate [15 kev/s] * [1/3] * [2] = 10 kev/s Equipment Duty Factor Raw Rate Duplication Factor 10 kev/s * 5 CPU-ms/ev = 50 CPU’s

Required Sustained Simulation Rate 5 kev/s * 100 CPU-ms/ev = 500 CPU’s [15 kev/s] * [1/3] * [10] * [1/10] = 5 kev/s Equipment Duty Factor Raw Rate Systematics Studies Good Event Fraction PWA error is determined by one’s knowledge of systematic errors. This requires extensive simulations, but not all events simulated are accepted events.

Annual Date Rate to Archive Raw Data 75 MB/sec * (3 *10 7 s/yr) * (1/3)= 0.75 PB/yr Simulation Data 25 MB/sec * (3 *10 7 s/yr) = 0.75 PB/yr Reconstructed Data 50 MB/sec * (3 *10 7 s/yr) = 1.50 PB/yr Total Rate to Archive ~ 3 PB/yr

Requirements Summary

Some comparisons: Hall D vs. other HENP Data Volumes (tape) TB/year Data rates MB/s Disk Cache TB CPU SI95/year People CMS2 000 (total) ~1800 US Atlas (Tier 1) ~500 (?) STAR20040>207000~300 D0/CDF Run II 300~500 BaBar300~500 Not just an issue of equipment. These experiments all have the support of large dedicated computing groups within the experiments well defined computing models JLAB– current ~240 (CLAS) Hall D

April 16, 2001L. Dennis, FSU Proposed Solution “You can’t always get what you want. You can’t always get what you want. But if you try sometimes, well you just might find You’ll get what you need.” Rolling Stones, You can’t always get what you want.

Meeting the Hall D Computational Challenges Moore’s law: Computer performance increases by a factor of 2 every 18 months. Gilder’s Law: Network bandwidth triples every 12 months. Solving the information management problems requires people working on the software and developing a workable computing environment. Dennis’ Law: Neither Moore’s Law nor Gilder’s Law will solve our computing problems.

Hall D Computing Tasks First Pass Analysis Data Mining Physics Analysis Partial Wave Analysis Physics Analysis Acquisition Monitoring Slow Controls Data Archival Planning Simulation Publication Calibrations

Initial Estimate of Software Tasks & Timeline

Hall D Grid

Hall D Grid Sites First Pass Analysis (Jefferson Lab) Simulation Sites (3-5) Physics Analysis Sites (3-5) Partial Wave Analysis Sites (2) Calibration Site

Hall D Offline Data Flow

Grid Efficiency Considerations Need extensive resources. Need universal access. Need good workflow. Need good communication about what has been done and what needs to be done.