# Presentation: 266963

## Distributed Data Access and Resource Management in the D0 SAM System

- Terekhov, *Fermi National Accelerator Laboratory,*for the SAM project:L.Carpenter, L.Lueking, C.Moore, J.Trumbo, S.Veseli, M.Vranicar, S.White, V.White

## Plan of Attack

- The domain
- D0 overview and applications
- SAM as a Data Grid
- Metadata
- File replication
- Initial resource management
- SAM and generic Grid technologies
- Comprehensive resource management

## D0: A Virtual Organization

- High Energy Physics (HEP) collider experiment, multi-institutional
- Collaboration of 500+ scientists, 72+ institutions, 18+ countries
- Physicists generate, analyze data
- Coordinated resource sharing (networks, MSS, etc) for common problem (physics analysis) solving

## Applications and Data Intensity

- Real data taking from the detector
- Monte-Carlo data simulation
- Reconstruction
- Analysis
- The gist of experimental HEP
- Extremely I/O intensive
- Recurrent processing of datasets: caching highly beneficial

## Applications and Data Intensity

- Real data taking from the detector
- The only irreplaceable data
- 250KB/event, D0-specific format
- 50 Hertz rate of recording
- By itself, not extremely data-intensive
- Not the motivation for Grid technologies

## Applications and Data Intensity, cont’d

- Monte-Carlo data simulation
- Generates a stream or rich simulated events
- Used to develop and validate physics scientific algorithms
- Also CPU-intensive
- Finite lifetime? Real data processing eventually takes over

## Applications and Data Intensity, cont’d

- Monte-Carlo data simulation
- Generates a stream or rich simulated events
- Used to develop and validate physics scientific algorithms
- Also CPU-intensive
- Finite lifetime? Real data processing eventually takes over

## Data Handling as the Core of D0 Meta-Computing

- HEP Applications are data-intensive (see below)
- Computational Economy is extremely data-centric b/c costs are driven by DH resources
- SAM: primarily and historically a DH system: a working *Data Grid* prototype
- Job control inclusion is in the Grid context (the D0-PPDG project)

## SAM as a Data Grid

- Mass Storage Systems

- Metadata

- Resource Management

- Data Replication

- Replica Selection

- Comprehensive Resource Management

- Replication Cost Estimation

- Generic Grid
- Services

- (External to SAM)

- Based on: A.Chervenak, I.Foster, C. Kesselman, C.Salisbury, S.Tuecke,
*The Data Grid: Towards an Architecture for the Distributed Management*
*And Analysis of Large Scientific Datasets,*
- To appear in Journal of Network and Computer Applications

- Core
- Services

- High Level
- Services

## Standard Grid Metadata

- Application metadata
- creation info and processing history
- data types (tiers, streams, etc D0-specific)
- files are self-describing
- Replica metadata
- each file has zero or more *locations*
- volume ID’s and location details for RM - part of the interface with Mass Storage System

## Standard Grid Metadata, cont’d

- System Configuration Metadata
- HW configuration: locations and capacities of disks and tapes (network and disk bandwidths)
- resource ownership and allocation:
- partition of disk, MSS bandwidths, etc by group
- fair shares parameters for resource allocation and job scheduling (FSAS)
- cost criteria (weight factors) for FSAS

## Advanced Metadata

- Dataset management (to a great advantage of the user)
- Job history (crash recovery mechanisms)
- File replica access history (used by RM)
- Resource utilization history (persistency in RM and accountability)
- See our complete data model for more details

## Data Replica Management

- Processing *Station*  is a (locally distributed, semi-autonomous) collection of HW resources (disk, CPU, etc). A SW component
- Local data replication for parallel processing in a single batch system - within a Station
- Global data replication - worldwide data exchange among Stations and MSS’s

## Local Data Replication

- consider a cluster, physically distributed disk *cache*
- logical partitioning by research groups
- each group executes independent cache replacement algorithm (FIFO, LRU, many flavors)
- Replica catalog is updated in the course of the cache replacement
- Access history of each local replica is maintained persistently in the MD

## Local Data Replication, cont’d

- While Resource Managers strive to have jobs and their data being in proximity (see below), the Batch System does not always dispatch jobs wherever the data lies
- Station executes *intra-cluster data replication * on demand, fully user-transparently

## Routing + Caching = Global Replication

**Replica**

**Site**

**WAN**

**Data flow**

**Station**

**Mass Storage System**

*Routing + Caching = Global Replication*

## Principles of Resource Management

- Implement experiment policies on prioritization and fair sharing in resource usage, by user categories (access modes, research group etc)
- Maximize throughput in terms of real work done (i.e. user jobs and not system internal jobs such as data transfers)

## Fair Sharing

- Allocation of resources and scheduling of jobs
- The goal is to ensure that, in a *busy* environment, each abstract user gets a fixed share of “resources” or gets a fixed share of “work” done

## FS and Computational Economy

- Jobs, when executed, incur *costs* (through resource utilization) and realize *benefits* (through getting work done)
- Maintain a tuple (vector) of cumulative costs/benefits for each abstract user and compare them to his allocated *fair share *to set priority higher/lower
- Incorporated all known resource types and benefit metrics, totally flexible

## The Hierarchy of Resource Managers

- Global RM

- Sites
- Connected
- by WAN

- Stations
- And MSS’s
- Connected
- By LANs

- Batch
- queues
- and disks

- Site RM

- Station –
- Local RM

- Experiment
- Policies,
- Fair Share
- Allocations,
- Cost
- Metrics

## Job Control: Station Integration with the Abstract Batch System

- Client

- Local RM
- (Station Master)

- Batch System

- Process Manager
- (SAM wrapper script)

- User Task

- Job Manager
- (Project Master)

- Sam submit

- submit

- dispatch

- invoke

- Sam condition satisfied

- resubmit

- setJobCount/stop

- invoke

- jobEnd

## SAM as a Data Grid

- Mass Storage Systems

- Metadata

- Resource Management

- Data Replication

- Replica Selection

- Comprehensive Resource Management

- Replication Cost Estimation

- (External to SAM)

- Core
- Services

- High Level
- Services

*Preferred*
*locations*

***Caching,***
***Forwarding,***
***Pinning***

***DH-Batch system integration,***
***Fair Share Allocation,***
***MSS access control***
***Network access control***

***Cached data,***
***File transfer queues,***
***Site RM weather conditions***

***Replica catalog,***
***System configuration,***
***Cost/Benefit metrics***

***Batch System internal RM***
***MSS internal RM***

- (External to SAM)

## SAM Grid Work (D0-PPDG)

- Enhance the system by adding Grid services (Grid authentication, replica selection, etc)
- Adapt the system to generic Grid services
- Replace proprietary tools and internal protocols with those standard to the Grid
- Collaborate with Computer Scientists to develop new Grid technologies, use SAM as a testbed for testing/validating them

## Initial PPDG Work: Condor/SAM Job Scheduling, Preliminary Architecture

*Initial PPDG Work: Condor/SAM Job Scheduling, Preliminary Architecture*

- Condor MMS

- Condor/SAM-Grid adapter

- Abstract Batch System

- Condor

- SAM/Condor-Grid adapter

- SAM

- SAM

- Sam submit

- Data and DH Resources

- Schedule Jobs

- Costs of job placements?

**Standard Grid**
**Protocols**

- CondorG

- Job Management

- Data Management

## Conclusions

- D0 SAM is not only a production meta-computing system, but a functioning Data Grid prototype, with data replication and resource management being in advanced/mature stage
- Work continues to fully Grid-enable the system
- Some of our components/services will hopefully be of interest to the Grid community