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  • Game Development World Championship 2013 for all game developers

    - by Hanhviope
    Interested in games and programming? Want to be visible in global game industry? Missing Viope Game Programming Contest 2012? Want to win a trip to Finland, visit top game studio and other attractive rewards? This is your CHANCE! Viope Solutions proudly announces Game Development World Championship 2013, as a sequel of successful Viope Game Programming Contest 2012 WHAT? The contest is organized by Viope Solutions. Students and freelancers are invited to compete in different categories. Participants can compete for Computer/Console game or Mobile Phone game. The competition involves partners and judges from Rovio, Microsoft, Unity, ArtiGames, Housemarque, Redlynx, Remedy, GrandCru, GameReactor and IGDA WHO? The contest is open to everyone around the world. WHERE? The submission of your game will be done via Viope World e-learning platform. WHEN? The contest is open from 08th October 2013 till 26th January 2014. HOW? Individuals and team of up to 4 members can register through our website. For information, please visit website www.viope.com/contest WE CHALLENGE YOU TO CREATE THE BEST GAMES EVER! Share this to all your friends who would be interested in this contest!

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  • World Record Performance on PeopleSoft Enterprise Financials Benchmark on SPARC T4-2

    - by Brian
    Oracle's SPARC T4-2 server achieved World Record performance on Oracle's PeopleSoft Enterprise Financials 9.1 executing 20 Million Journals lines in 8.92 minutes on Oracle Database 11g Release 2 running on Oracle Solaris 11. This is the first result published on this version of the benchmark. The SPARC T4-2 server was able to process 20 million general ledger journal edit and post batch jobs in 8.92 minutes on this benchmark that reflects a large customer environment that utilizes a back-end database of nearly 500 GB. This benchmark demonstrates that the SPARC T4-2 server with PeopleSoft Financials 9.1 can easily process 100 million journal lines in less than 1 hour. The SPARC T4-2 server delivered more than 146 MB/sec of IO throughput with Oracle Database 11g running on Oracle Solaris 11. Performance Landscape Results are presented for PeopleSoft Financials Benchmark 9.1. Results obtained with PeopleSoft Financials Benchmark 9.1 are not comparable to the the previous version of the benchmark, PeopleSoft Financials Benchmark 9.0, due to significant change in data model and supports only batch. PeopleSoft Financials Benchmark, Version 9.1 Solution Under Test Batch (min) SPARC T4-2 (2 x SPARC T4, 2.85 GHz) 8.92 Results from PeopleSoft Financials Benchmark 9.0. PeopleSoft Financials Benchmark, Version 9.0 Solution Under Test Batch (min) Batch with Online (min) SPARC Enterprise M4000 (Web/App) SPARC Enterprise M5000 (DB) 33.09 34.72 SPARC T3-1 (Web/App) SPARC Enterprise M5000 (DB) 35.82 37.01 Configuration Summary Hardware Configuration: 1 x SPARC T4-2 server 2 x SPARC T4 processors, 2.85 GHz 128 GB memory Storage Configuration: 1 x Sun Storage F5100 Flash Array (for database and redo logs) 2 x Sun Storage 2540-M2 arrays and 2 x Sun Storage 2501-M2 arrays (for backup) Software Configuration: Oracle Solaris 11 11/11 SRU 7.5 Oracle Database 11g Release 2 (11.2.0.3) PeopleSoft Financials 9.1 Feature Pack 2 PeopleSoft Supply Chain Management 9.1 Feature Pack 2 PeopleSoft PeopleTools 8.52 latest patch - 8.52.03 Oracle WebLogic Server 10.3.5 Java Platform, Standard Edition Development Kit 6 Update 32 Benchmark Description The PeopleSoft Enterprise Financials 9.1 benchmark emulates a large enterprise that processes and validates a large number of financial journal transactions before posting the journal entry to the ledger. The validation process certifies that the journal entries are accurate, ensuring that ChartFields values are valid, debits and credits equal out, and inter/intra-units are balanced. Once validated, the entries are processed, ensuring that each journal line posts to the correct target ledger, and then changes the journal status to posted. In this benchmark, the Journal Edit & Post is set up to edit and post both Inter-Unit and Regular multi-currency journals. The benchmark processes 20 million journal lines using AppEngine for edits and Cobol for post processes. See Also Oracle PeopleSoft Benchmark White Papers oracle.com SPARC T4-2 Server oracle.com OTN PeopleSoft Financial Management oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 1 October 2012.

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  • SPARC T4-4 Delivers World Record First Result on PeopleSoft Combined Benchmark

    - by Brian
    Oracle's SPARC T4-4 servers running Oracle's PeopleSoft HCM 9.1 combined online and batch benchmark achieved World Record 18,000 concurrent users while executing a PeopleSoft Payroll batch job of 500,000 employees in 43.32 minutes and maintaining online users response time at < 2 seconds. This world record is the first to run online and batch workloads concurrently. This result was obtained with a SPARC T4-4 server running Oracle Database 11g Release 2, a SPARC T4-4 server running PeopleSoft HCM 9.1 application server and a SPARC T4-2 server running Oracle WebLogic Server in the web tier. The SPARC T4-4 server running the application tier used Oracle Solaris Zones which provide a flexible, scalable and manageable virtualization environment. The average CPU utilization on the SPARC T4-2 server in the web tier was 17%, on the SPARC T4-4 server in the application tier it was 59%, and on the SPARC T4-4 server in the database tier was 35% (online and batch) leaving significant headroom for additional processing across the three tiers. The SPARC T4-4 server used for the database tier hosted Oracle Database 11g Release 2 using Oracle Automatic Storage Management (ASM) for database files management with I/O performance equivalent to raw devices. This is the first three tier mixed workload (online and batch) PeopleSoft benchmark also processing PeopleSoft payroll batch workload. Performance Landscape PeopleSoft HR Self-Service and Payroll Benchmark Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-2 (web) SPARC T4-4 (app) SPARC T4-2 (db) 18,000 0.944 0.503 43.32 64 Configuration Summary Application Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 512 GB memory 5 x 300 GB SAS internal disks 1 x 100 GB and 2 x 300 GB internal SSDs 2 x 10 Gbe HBA Oracle Solaris 11 11/11 PeopleTools 8.52 PeopleSoft HCM 9.1 Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031 Java Platform, Standard Edition Development Kit 6 Update 32 Database Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 256 GB memory 3 x 300 GB SAS internal disks Oracle Solaris 11 11/11 Oracle Database 11g Release 2 Web Tier Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 2 x 300 GB SAS internal disks 1 x 100 GB internal SSD Oracle Solaris 11 11/11 PeopleTools 8.52 Oracle WebLogic Server 10.3.4 Java Platform, Standard Edition Development Kit 6 Update 32 Storage Configuration: 1 x Sun Server X2-4 as a COMSTAR head for data 4 x Intel Xeon X7550, 2.0 GHz 128 GB memory 1 x Sun Storage F5100 Flash Array (80 flash modules) 1 x Sun Storage F5100 Flash Array (40 flash modules) 1 x Sun Fire X4275 as a COMSTAR head for redo logs 12 x 2 TB SAS disks with Niwot Raid controller Benchmark Description This benchmark combines PeopleSoft HCM 9.1 HR Self Service online and PeopleSoft Payroll batch workloads to run on a unified database deployed on Oracle Database 11g Release 2. The PeopleSoft HRSS benchmark kit is a Oracle standard benchmark kit run by all platform vendors to measure the performance. It's an OLTP benchmark where DB SQLs are moderately complex. The results are certified by Oracle and a white paper is published. PeopleSoft HR SS defines a business transaction as a series of HTML pages that guide a user through a particular scenario. Users are defined as corporate Employees, Managers and HR administrators. The benchmark consist of 14 scenarios which emulate users performing typical HCM transactions such as viewing paycheck, promoting and hiring employees, updating employee profile and other typical HCM application transactions. All these transactions are well-defined in the PeopleSoft HR Self-Service 9.1 benchmark kit. This benchmark metric is the weighted average response search/save time for all the transactions. The PeopleSoft 9.1 Payroll (North America) benchmark demonstrates system performance for a range of processing volumes in a specific configuration. This workload represents large batch runs typical of a ERP environment during a mass update. The benchmark measures five application business process run times for a database representing large organization. They are Paysheet Creation, Payroll Calculation, Payroll Confirmation, Print Advice forms, and Create Direct Deposit File. The benchmark metric is the cumulative elapsed time taken to complete the Paysheet Creation, Payroll Calculation and Payroll Confirmation business application processes. The benchmark metrics are taken for each respective benchmark while running simultaneously on the same database back-end. Specifically, the payroll batch processes are started when the online workload reaches steady state (the maximum number of online users) and overlap with online transactions for the duration of the steady state. Key Points and Best Practices Two Oracle PeopleSoft Domain sets with 200 application servers each on a SPARC T4-4 server were hosted in 2 separate Oracle Solaris Zones to demonstrate consolidation of multiple application servers, ease of administration and performance tuning. Each Oracle Solaris Zone was bound to a separate processor set, each containing 15 cores (total 120 threads). The default set (1 core from first and third processor socket, total 16 threads) was used for network and disk interrupt handling. This was done to improve performance by reducing memory access latency by using the physical memory closest to the processors and offload I/O interrupt handling to default set threads, freeing up cpu resources for Application Servers threads and balancing application workload across 240 threads. See Also Oracle PeopleSoft Benchmark White Papers oracle.com SPARC T4-2 Server oracle.com OTN SPARC T4-4 Server oracle.com OTN PeopleSoft Enterprise Human Capital Management oracle.com OTN PeopleSoft Enterprise Human Capital Management (Payroll) oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Oracle's PeopleSoft HR and Payroll combined benchmark, www.oracle.com/us/solutions/benchmark/apps-benchmark/peoplesoft-167486.html, results 09/30/2012.

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  • Improved Performance on PeopleSoft Combined Benchmark using SPARC T4-4

    - by Brian
    Oracle's SPARC T4-4 server running Oracle's PeopleSoft HCM 9.1 combined online and batch benchmark achieved a world record 18,000 concurrent users experiencing subsecond response time while executing a PeopleSoft Payroll batch job of 500,000 employees in 32.4 minutes. This result was obtained with a SPARC T4-4 server running Oracle Database 11g Release 2, a SPARC T4-4 server running PeopleSoft HCM 9.1 application server and a SPARC T4-2 server running Oracle WebLogic Server in the web tier. The SPARC T4-4 server running the application tier used Oracle Solaris Zones which provide a flexible, scalable and manageable virtualization environment. The average CPU utilization on the SPARC T4-2 server in the web tier was 17%, on the SPARC T4-4 server in the application tier it was 59%, and on the SPARC T4-4 server in the database tier was 47% (online and batch) leaving significant headroom for additional processing across the three tiers. The SPARC T4-4 server used for the database tier hosted Oracle Database 11g Release 2 using Oracle Automatic Storage Management (ASM) for database files management with I/O performance equivalent to raw devices. Performance Landscape Results are presented for the PeopleSoft HRMS Self-Service and Payroll combined benchmark. The new result with 128 streams shows significant improvement in the payroll batch processing time with little impact on the self-service component response time. PeopleSoft HRMS Self-Service and Payroll Benchmark Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-2 (web) SPARC T4-4 (app) SPARC T4-4 (db) 18,000 0.988 0.539 32.4 128 SPARC T4-2 (web) SPARC T4-4 (app) SPARC T4-4 (db) 18,000 0.944 0.503 43.3 64 The following results are for the PeopleSoft HRMS Self-Service benchmark that was previous run. The results are not directly comparable with the combined results because they do not include the payroll component. PeopleSoft HRMS Self-Service 9.1 Benchmark Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-2 (web) SPARC T4-4 (app) 2x SPARC T4-2 (db) 18,000 1.048 0.742 N/A N/A The following results are for the PeopleSoft Payroll benchmark that was previous run. The results are not directly comparable with the combined results because they do not include the self-service component. PeopleSoft Payroll (N.A.) 9.1 - 500K Employees (7 Million SQL PayCalc, Unicode) Systems Users Ave Response Search (sec) Ave Response Save (sec) Batch Time (min) Streams SPARC T4-4 (db) N/A N/A N/A 30.84 96 Configuration Summary Application Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 512 GB memory Oracle Solaris 11 11/11 PeopleTools 8.52 PeopleSoft HCM 9.1 Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031 Java Platform, Standard Edition Development Kit 6 Update 32 Database Configuration: 1 x SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 256 GB memory Oracle Solaris 11 11/11 Oracle Database 11g Release 2 PeopleTools 8.52 Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031 Micro Focus Server Express (COBOL v 5.1.00) Web Tier Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory Oracle Solaris 11 11/11 PeopleTools 8.52 Oracle WebLogic Server 10.3.4 Java Platform, Standard Edition Development Kit 6 Update 32 Storage Configuration: 1 x Sun Server X2-4 as a COMSTAR head for data 4 x Intel Xeon X7550, 2.0 GHz 128 GB memory 1 x Sun Storage F5100 Flash Array (80 flash modules) 1 x Sun Storage F5100 Flash Array (40 flash modules) 1 x Sun Fire X4275 as a COMSTAR head for redo logs 12 x 2 TB SAS disks with Niwot Raid controller Benchmark Description This benchmark combines PeopleSoft HCM 9.1 HR Self Service online and PeopleSoft Payroll batch workloads to run on a unified database deployed on Oracle Database 11g Release 2. The PeopleSoft HRSS benchmark kit is a Oracle standard benchmark kit run by all platform vendors to measure the performance. It's an OLTP benchmark where DB SQLs are moderately complex. The results are certified by Oracle and a white paper is published. PeopleSoft HR SS defines a business transaction as a series of HTML pages that guide a user through a particular scenario. Users are defined as corporate Employees, Managers and HR administrators. The benchmark consist of 14 scenarios which emulate users performing typical HCM transactions such as viewing paycheck, promoting and hiring employees, updating employee profile and other typical HCM application transactions. All these transactions are well-defined in the PeopleSoft HR Self-Service 9.1 benchmark kit. This benchmark metric is the weighted average response search/save time for all the transactions. The PeopleSoft 9.1 Payroll (North America) benchmark demonstrates system performance for a range of processing volumes in a specific configuration. This workload represents large batch runs typical of a ERP environment during a mass update. The benchmark measures five application business process run times for a database representing large organization. They are Paysheet Creation, Payroll Calculation, Payroll Confirmation, Print Advice forms, and Create Direct Deposit File. The benchmark metric is the cumulative elapsed time taken to complete the Paysheet Creation, Payroll Calculation and Payroll Confirmation business application processes. The benchmark metrics are taken for each respective benchmark while running simultaneously on the same database back-end. Specifically, the payroll batch processes are started when the online workload reaches steady state (the maximum number of online users) and overlap with online transactions for the duration of the steady state. Key Points and Best Practices Two PeopleSoft Domain sets with 200 application servers each on a SPARC T4-4 server were hosted in 2 separate Oracle Solaris Zones to demonstrate consolidation of multiple application servers, ease of administration and performance tuning. Each Oracle Solaris Zone was bound to a separate processor set, each containing 15 cores (total 120 threads). The default set (1 core from first and third processor socket, total 16 threads) was used for network and disk interrupt handling. This was done to improve performance by reducing memory access latency by using the physical memory closest to the processors and offload I/O interrupt handling to default set threads, freeing up cpu resources for Application Servers threads and balancing application workload across 240 threads. A total of 128 PeopleSoft streams server processes where used on the database node to complete payroll batch job of 500,000 employees in 32.4 minutes. See Also Oracle PeopleSoft Benchmark White Papers oracle.com SPARC T4-2 Server oracle.com OTN SPARC T4-4 Server oracle.com OTN PeopleSoft Enterprise Human Capital Managementoracle.com OTN PeopleSoft Enterprise Human Capital Management (Payroll) oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 8 November 2012.

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  • World Record Oracle Business Intelligence Benchmark on SPARC T4-4

    - by Brian
    Oracle's SPARC T4-4 server configured with four SPARC T4 3.0 GHz processors delivered the first and best performance of 25,000 concurrent users on Oracle Business Intelligence Enterprise Edition (BI EE) 11g benchmark using Oracle Database 11g Release 2 running on Oracle Solaris 10. A SPARC T4-4 server running Oracle Business Intelligence Enterprise Edition 11g achieved 25,000 concurrent users with an average response time of 0.36 seconds with Oracle BI server cache set to ON. The benchmark data clearly shows that the underlying hardware, SPARC T4 server, and the Oracle BI EE 11g (11.1.1.6.0 64-bit) platform scales within a single system supporting 25,000 concurrent users while executing 415 transactions/sec. The benchmark demonstrated the scalability of Oracle Business Intelligence Enterprise Edition 11g 11.1.1.6.0, which was deployed in a vertical scale-out fashion on a single SPARC T4-4 server. Oracle Internet Directory configured on SPARC T4 server provided authentication for the 25,000 Oracle BI EE users with sub-second response time. A SPARC T4-4 with internal Solid State Drive (SSD) using the ZFS file system showed significant I/O performance improvement over traditional disk for the Web Catalog activity. In addition, ZFS helped get past the UFS limitation of 32767 sub-directories in a Web Catalog directory. The multi-threaded 64-bit Oracle Business Intelligence Enterprise Edition 11g and SPARC T4-4 server proved to be a successful combination by providing sub-second response times for the end user transactions, consuming only half of the available CPU resources at 25,000 concurrent users, leaving plenty of head room for increased load. The Oracle Business Intelligence on SPARC T4-4 server benchmark results demonstrate that comprehensive BI functionality built on a unified infrastructure with a unified business model yields best-in-class scalability, reliability and performance. Oracle BI EE 11g is a newer version of Business Intelligence Suite with richer and superior functionality. Results produced with Oracle BI EE 11g benchmark are not comparable to results with Oracle BI EE 10g benchmark. Oracle BI EE 11g is a more difficult benchmark to run, exercising more features of Oracle BI. Performance Landscape Results for the Oracle BI EE 11g version of the benchmark. Results are not comparable to the Oracle BI EE 10g version of the benchmark. Oracle BI EE 11g Benchmark System Number of Users Response Time (sec) 1 x SPARC T4-4 (4 x SPARC T4 3.0 GHz) 25,000 0.36 Results for the Oracle BI EE 10g version of the benchmark. Results are not comparable to the Oracle BI EE 11g version of the benchmark. Oracle BI EE 10g Benchmark System Number of Users 2 x SPARC T5440 (4 x SPARC T2+ 1.6 GHz) 50,000 1 x SPARC T5440 (4 x SPARC T2+ 1.6 GHz) 28,000 Configuration Summary Hardware Configuration: SPARC T4-4 server 4 x SPARC T4-4 processors, 3.0 GHz 128 GB memory 4 x 300 GB internal SSD Storage Configuration: "> Sun ZFS Storage 7120 16 x 146 GB disks Software Configuration: Oracle Solaris 10 8/11 Oracle Solaris Studio 12.1 Oracle Business Intelligence Enterprise Edition 11g (11.1.1.6.0) Oracle WebLogic Server 10.3.5 Oracle Internet Directory 11.1.1.6.0 Oracle Database 11g Release 2 Benchmark Description Oracle Business Intelligence Enterprise Edition (Oracle BI EE) delivers a robust set of reporting, ad-hoc query and analysis, OLAP, dashboard, and scorecard functionality with a rich end-user experience that includes visualization, collaboration, and more. The Oracle BI EE benchmark test used five different business user roles - Marketing Executive, Sales Representative, Sales Manager, Sales Vice-President, and Service Manager. These roles included a maximum of 5 different pre-built dashboards. Each dashboard page had an average of 5 reports in the form of a mix of charts, tables and pivot tables, returning anywhere from 50 rows to approximately 500 rows of aggregated data. The test scenario also included drill-down into multiple levels from a table or chart within a dashboard. The benchmark test scenario uses a typical business user sequence of dashboard navigation, report viewing, and drill down. For example, a Service Manager logs into the system and navigates to his own set of dashboards using Service Manager. The BI user selects the Service Effectiveness dashboard, which shows him four distinct reports, Service Request Trend, First Time Fix Rate, Activity Problem Areas, and Cost Per Completed Service Call spanning 2002 to 2005. The user then proceeds to view the Customer Satisfaction dashboard, which also contains a set of 4 related reports, drills down on some of the reports to see the detail data. The BI user continues to view more dashboards – Customer Satisfaction and Service Request Overview, for example. After navigating through those dashboards, the user logs out of the application. The benchmark test is executed against a full production version of the Oracle Business Intelligence 11g Applications with a fully populated underlying database schema. The business processes in the test scenario closely represent a real world customer scenario. See Also SPARC T4-4 Server oracle.com OTN Oracle Business Intelligence oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN WebLogic Suite oracle.com OTN Oracle Solaris oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 30 September 2012.

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  • Creating ground in a 2D runner game

    - by user739711
    It may be a repetitive uestion but I could not find any specific answer to my query How to create A slanted/curved ground in a 2d runner game. The user will see side view like the old game "Mario" If I use tiled based map I can have only rectangular objects. What is the best way to create tilted ground? Should I use tiled based map, or should I define corner points in the map and create the ground programatically? And what are the difficulties in creating curved ground.

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  • The Game vs The Game Engine?

    - by Milo
    I was wondering if somebody could tell me how the game and the game engine fit into game development. Specifically what I mean is, the game engine does not actually have a game. So where I'm unclear about is basically, do game developpers build an engine, then create a new class that inherits from engine which becomes the game? Ex: class ShooterGame : public Engine { }; So basically i'm unclear on where the game code fits into the engine. Thanks

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  • Making A C++ Game

    - by user1758938
    I'm gonna make a game and I think C++ would be perfect for it. I think I'm gonna use SDL and OpenGL but I need help with making the code manageable. These were my ideas: 1. Making A DLL File With Commands Such A CreateScreen(640, 480); Which Binds SDL And OpenGL Commands For A Manageable Setup 2. Making It Harder To Mod (Like UnCompiling My Code) Like Encrypting Save Files That Only My Program Can Read Any Suggestions?

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  • SPARC T4-4 Beats 8-CPU IBM POWER7 on TPC-H @3000GB Benchmark

    - by Brian
    Oracle's SPARC T4-4 server delivered a world record TPC-H @3000GB benchmark result for systems with four processors. This result beats eight processor results from IBM (POWER7) and HP (x86). The SPARC T4-4 server also delivered better performance per core than these eight processor systems from IBM and HP. Comparisons below are based upon system to system comparisons, highlighting Oracle's complete software and hardware solution. This database world record result used Oracle's Sun Storage 2540-M2 arrays (rotating disk) connected to a SPARC T4-4 server running Oracle Solaris 11 and Oracle Database 11g Release 2 demonstrating the power of Oracle's integrated hardware and software solution. The SPARC T4-4 server based configuration achieved a TPC-H scale factor 3000 world record for four processor systems of 205,792 QphH@3000GB with price/performance of $4.10/QphH@3000GB. The SPARC T4-4 server with four SPARC T4 processors (total of 32 cores) is 7% faster than the IBM Power 780 server with eight POWER7 processors (total of 32 cores) on the TPC-H @3000GB benchmark. The SPARC T4-4 server is 36% better in price performance compared to the IBM Power 780 server on the TPC-H @3000GB Benchmark. The SPARC T4-4 server is 29% faster than the IBM Power 780 for data loading. The SPARC T4-4 server is up to 3.4 times faster than the IBM Power 780 server for the Refresh Function. The SPARC T4-4 server with four SPARC T4 processors is 27% faster than the HP ProLiant DL980 G7 server with eight x86 processors on the TPC-H @3000GB benchmark. The SPARC T4-4 server is 52% faster than the HP ProLiant DL980 G7 server for data loading. The SPARC T4-4 server is up to 3.2 times faster than the HP ProLiant DL980 G7 for the Refresh Function. The SPARC T4-4 server achieved a peak IO rate from the Oracle database of 17 GB/sec. This rate was independent of the storage used, as demonstrated by the TPC-H @3000TB benchmark which used twelve Sun Storage 2540-M2 arrays (rotating disk) and the TPC-H @1000TB benchmark which used four Sun Storage F5100 Flash Array devices (flash storage). [*] The SPARC T4-4 server showed linear scaling from TPC-H @1000GB to TPC-H @3000GB. This demonstrates that the SPARC T4-4 server can handle the increasingly larger databases required of DSS systems. [*] The SPARC T4-4 server benchmark results demonstrate a complete solution of building Decision Support Systems including data loading, business questions and refreshing data. Each phase usually has a time constraint and the SPARC T4-4 server shows superior performance during each phase. [*] The TPC believes that comparisons of results published with different scale factors are misleading and discourages such comparisons. Performance Landscape The table lists the leading TPC-H @3000GB results for non-clustered systems. TPC-H @3000GB, Non-Clustered Systems System Processor P/C/T – Memory Composite(QphH) $/perf($/QphH) Power(QppH) Throughput(QthH) Database Available SPARC Enterprise M9000 3.0 GHz SPARC64 VII+ 64/256/256 – 1024 GB 386,478.3 $18.19 316,835.8 471,428.6 Oracle 11g R2 09/22/11 SPARC T4-4 3.0 GHz SPARC T4 4/32/256 – 1024 GB 205,792.0 $4.10 190,325.1 222,515.9 Oracle 11g R2 05/31/12 SPARC Enterprise M9000 2.88 GHz SPARC64 VII 32/128/256 – 512 GB 198,907.5 $15.27 182,350.7 216,967.7 Oracle 11g R2 12/09/10 IBM Power 780 4.1 GHz POWER7 8/32/128 – 1024 GB 192,001.1 $6.37 210,368.4 175,237.4 Sybase 15.4 11/30/11 HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 8/64/128 – 512 GB 162,601.7 $2.68 185,297.7 142,685.6 SQL Server 2008 10/13/10 P/C/T = Processors, Cores, Threads QphH = the Composite Metric (bigger is better) $/QphH = the Price/Performance metric in USD (smaller is better) QppH = the Power Numerical Quantity QthH = the Throughput Numerical Quantity The following table lists data load times and refresh function times during the power run. TPC-H @3000GB, Non-Clustered Systems Database Load & Database Refresh System Processor Data Loading(h:m:s) T4Advan RF1(sec) T4Advan RF2(sec) T4Advan SPARC T4-4 3.0 GHz SPARC T4 04:08:29 1.0x 67.1 1.0x 39.5 1.0x IBM Power 780 4.1 GHz POWER7 05:51:50 1.5x 147.3 2.2x 133.2 3.4x HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 08:35:17 2.1x 173.0 2.6x 126.3 3.2x Data Loading = database load time RF1 = power test first refresh transaction RF2 = power test second refresh transaction T4 Advan = the ratio of time to T4 time Complete benchmark results found at the TPC benchmark website http://www.tpc.org. Configuration Summary and Results Hardware Configuration: SPARC T4-4 server 4 x SPARC T4 3.0 GHz processors (total of 32 cores, 128 threads) 1024 GB memory 8 x internal SAS (8 x 300 GB) disk drives External Storage: 12 x Sun Storage 2540-M2 array storage, each with 12 x 15K RPM 300 GB drives, 2 controllers, 2 GB cache Software Configuration: Oracle Solaris 11 11/11 Oracle Database 11g Release 2 Enterprise Edition Audited Results: Database Size: 3000 GB (Scale Factor 3000) TPC-H Composite: 205,792.0 QphH@3000GB Price/performance: $4.10/QphH@3000GB Available: 05/31/2012 Total 3 year Cost: $843,656 TPC-H Power: 190,325.1 TPC-H Throughput: 222,515.9 Database Load Time: 4:08:29 Benchmark Description The TPC-H benchmark is a performance benchmark established by the Transaction Processing Council (TPC) to demonstrate Data Warehousing/Decision Support Systems (DSS). TPC-H measurements are produced for customers to evaluate the performance of various DSS systems. These queries and updates are executed against a standard database under controlled conditions. Performance projections and comparisons between different TPC-H Database sizes (100GB, 300GB, 1000GB, 3000GB, 10000GB, 30000GB and 100000GB) are not allowed by the TPC. TPC-H is a data warehousing-oriented, non-industry-specific benchmark that consists of a large number of complex queries typical of decision support applications. It also includes some insert and delete activity that is intended to simulate loading and purging data from a warehouse. TPC-H measures the combined performance of a particular database manager on a specific computer system. The main performance metric reported by TPC-H is called the TPC-H Composite Query-per-Hour Performance Metric (QphH@SF, where SF is the number of GB of raw data, referred to as the scale factor). QphH@SF is intended to summarize the ability of the system to process queries in both single and multiple user modes. The benchmark requires reporting of price/performance, which is the ratio of the total HW/SW cost plus 3 years maintenance to the QphH. A secondary metric is the storage efficiency, which is the ratio of total configured disk space in GB to the scale factor. Key Points and Best Practices Twelve Sun Storage 2540-M2 arrays were used for the benchmark. Each Sun Storage 2540-M2 array contains 12 15K RPM drives and is connected to a single dual port 8Gb FC HBA using 2 ports. Each Sun Storage 2540-M2 array showed 1.5 GB/sec for sequential read operations and showed linear scaling, achieving 18 GB/sec with twelve Sun Storage 2540-M2 arrays. These were stand alone IO tests. The peak IO rate measured from the Oracle database was 17 GB/sec. Oracle Solaris 11 11/11 required very little system tuning. Some vendors try to make the point that storage ratios are of customer concern. However, storage ratio size has more to do with disk layout and the increasing capacities of disks – so this is not an important metric in which to compare systems. The SPARC T4-4 server and Oracle Solaris efficiently managed the system load of over one thousand Oracle Database parallel processes. Six Sun Storage 2540-M2 arrays were mirrored to another six Sun Storage 2540-M2 arrays on which all of the Oracle database files were placed. IO performance was high and balanced across all the arrays. The TPC-H Refresh Function (RF) simulates periodical refresh portion of Data Warehouse by adding new sales and deleting old sales data. Parallel DML (parallel insert and delete in this case) and database log performance are a key for this function and the SPARC T4-4 server outperformed both the IBM POWER7 server and HP ProLiant DL980 G7 server. (See the RF columns above.) See Also Transaction Processing Performance Council (TPC) Home Page Ideas International Benchmark Page SPARC T4-4 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Sun Storage 2540-M2 Array oracle.com OTN Disclosure Statement TPC-H, QphH, $/QphH are trademarks of Transaction Processing Performance Council (TPC). For more information, see www.tpc.org. SPARC T4-4 205,792.0 QphH@3000GB, $4.10/QphH@3000GB, available 5/31/12, 4 processors, 32 cores, 256 threads; IBM Power 780 QphH@3000GB, 192,001.1 QphH@3000GB, $6.37/QphH@3000GB, available 11/30/11, 8 processors, 32 cores, 128 threads; HP ProLiant DL980 G7 162,601.7 QphH@3000GB, $2.68/QphH@3000GB available 10/13/10, 8 processors, 64 cores, 128 threads.

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  • Feedback on "market manipulation", a peripheral game mechanic for a satirical MMO

    - by BerndBrot
    This question asks for feedback on a specific game-mechanic. Since there is not one right feedback on a game mechanic, I tried to provide enough context and guidelines to still make it possible for users to rate answers and to accept an answer as the best answer (following these criteria from Writer.SE's meta website). Please comment if you have any suggestions on how I could improve the question in that regard. So, let's begin with the game itself and some of its elements which are relevant for this question. Context I'm working on a satirical, text-based multiplayer adventure and role-playing game set in modern-day London. The game resolves around the concept of sin and features a myriad of (venomous) allusions to all the things that go wrong in this world. Players can choose between character classes like bullshit artist (consultant), bankster, lawyer, mobster, celebrity, politician, etc. In order to complete the game, the player has to live so sinfully with regard to any of the seven deadly sins that a demon is willing to offer them a contract of sponsorship. On their quest to live a sinful live, characters explore more and more locations of modern-day London (on a GoogleMap), fight "monsters" like insurance sales agents or Jehovah's Witnesses, and complete quests, like building a PowerPoint presentation out of marketing buzz words or keeping up a number of substance abuse effects in order to progress on the gluttony path. Battles are turn based with both combatants having a deck of cards, with which they try to make their enemy give in to temptations of all sorts. Tempted enemies sometimes become contacts (an item drop mechanic), which can be exploited for various benefits, depending on their area of influence (finance, underworld, bureaucracy, etc.), level of influence, and kind of sway that the player has over them (bribed, seduced, threatened, etc.) Once a contract has been exploited, the player loses that contact. Most actions require turns. Turns are limited, but refill each day. Criteria A number of peripheral game mechanics are supposed to represent real world abuses and mischief in a humorous way integrate real world data and events to strengthen the feeling of relevance of the game's humor with regard to real world problems add fun ways of interacting with other players add ways for players to express themselves through game-play Market manipulation is one such peripheral game mechanic and should fulfill all of these goals. Market manipulation This is my initial design of the mechanic: Players can enter the London Stock Exchange (LSE) (without paying a turn) LSE displays the stock prices of a number of companies in industries like weapons or tobacco as well as some derivatives based on wheat and corn. The stock prices are calculated based on the actual stock prices of these companies and derivatives (in real time) any market manipulations that were conducted by the players any market corrections of the system Players can buy and sell shares with cash, a resource in the game, at current in-game market value (without paying a turn). Players can manipulate the market, i.e. let the price of a share either rise or fall, by some amount, over a certain period of time. Manipulating the market requires 1 turn A contact in the financial sector (see above). The higher the level of influence of the contact, the stronger the effect of the manipulation on the stock price, and/or the shorter it takes for the manipulation to manifest itself. Market manipulation also adds a crime to the player's record. (There are a multitude of ways to take care of that, but it is still another "cost" of market manipulations.) The system continuously corrects market manipulations by letting the in-game prices converge towards their real world counterparts at a rate of 2% of the difference between the two per hour. Because of this market correction mechanism, pushing up prices (and screwing down prices) becomes increasingly difficult the higher (lower) the price already is. Whenever food prices reach a certain level, in-game stories are posted about hunger catastrophes happening somewhere far, far away (maybe with links to real world news stories). Whenever a player sells a certain number of shares with a sufficiently high margin, they are mentioned in that day's in-game financial news. Since the number of stock options is very limited, players will inevitably collide in their efforts to manipulate the market in their favor. Hopefully, it will also be a fun side-arena for guilds and covenants to fight each other. Question(s) What do you think of this mechanism given the criteria for peripheral game mechanics that I specified for my game? Do you have any ideas how the mechanic could be improved with regard to these criteria (or otherwise)? Could it be improved to allow for more expressive game-play, or involve an allusion to some other real world madness (like short selling, leveraging, or some other banking magic)? Are there any game-theoretic problems with this mechanic, like maybe certain dominant individual strategies that, collectively, lead to every player profiting and thus eliminating the idea of market manipulation PVP? Also, if you like (or dislike) this question, feel free to participate in the discussion on GDSE meta: "Should we be more lax with regard to SE's question/answer format to make game design questions possible?"

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  • The right way to start out in game development/design [closed]

    - by Marco Sacristão
    Greetings everyone I'm a 19 year old student looking for some help in the field of game development. This question may or may not seem a bit overused, but the fact is that game development has been my life long dream, and after several hours of search I've realized that I've been going in circles for the past three or four months whilst doing such research on how to really get down and dirty with game development, therefor I decided to ask you guys if you could help me out at all. Let me start off with some information about me and things i've already learned about GameDev which might help you out on helping me out (wordplay!): I'm not an expert programmer, but I do have knowledge on how to program in several languages including C and Java (Currently learning Java in my degree in Computer Engineering), but my methodology might not be most correct in terms of syntax (hence my difficulty in starting out, i'm afraid that the starting point might not be the most correct, and it would deploy a wrongful development methodology that would be to corrected later on, in terms of game development or other projects). I have yet to work in a project as large as a game, never in my learning curve of programming I've done a project to the scale of a video game, only very small software (PHP Front-ends and Back-ends, with some basic JQuery and CSS knowledge). I'm not the biggest mathematician or physicist, but I already know that is not a problem, because there are several game engines already available for use and integration with home-made projects (Box2D, etc). I've also learned about some libraries that could be included in said projects, to ease out some process in game development, like SDL for example. I do not know how sprites, states, particles or any specific game-related techniques work. With that being said, you can see that I have some ideas on game development, but I have absolutely no clue on how to design and produce a game, or even how game-like mechanics work. It does not have to be a complex game just to start out, I'd rather learn the basic of game design (Like 2D drawing, tiling, object collision) and test that out in a language that I feel comfortable in which could be later on migrated to other platforms, as long that what I've learned is the correct way to do things, and not just something that I've learned from some guy on Youtube by replicating that code on the video. I'm sorry if my question is not in the best format possible, but I've got so many questions on my mind that are still un-answered that I don't know were to start! Thank you for reading.

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  • Effectively implementing a game view using java

    - by kdavis8
    I am writing a 2d game in java. The game mechanics are similar to the Pokémon game boy advance series e.g. fire red, ruby, diamond and so on. I need a way to draw a huge map maybe 5000 by 5000 pixels and then load individual in game sprites to across the entirety of the map, like rendering a scene. Game sprites would be things like terrain objects, trees, rocks, bushes, also houses, castles, NPC's and so on. But i also need to implement some kind of camera view class that focuses on the player. the camera view class needs to follow the characters movements throughout the game map but it also needs to clip the rest of the map away from the user's field of view, so that the user can only see the arbitrary proximity adjacent to the player's sprite. The proximity's range could be something like 500 pixels in every direction around the player’s sprite. On top of this, i need to implement an independent resolution for the game world so that the game view will be uniform on all screen sizes and screen resolutions. I know that this does sound like a handful and may fall under the category of multiple questions, but the questions are all related and any advice would be very much appreciated. I don’t need a full source code listing but maybe some pointers to effective java API classes that could make doing what i need to do a lot simpler. Also any algorithmic/ design advice would greatly benefit me as well. example of what i am trying to do in source code form below package myPackage; /** * The Purpose of GameView is to: Render a scene using Scene class, Create a * clipping pane using CameraView class, and finally instantiate a coordinate * grid using Path class. * * Once all of these things have been done, GameView class should then be * instantiated and used jointly with its helper classes. CameraView should be * used as the main drawing image. CameraView is the the window to the game * world.Scene passes data constantly to CameraView so that the entire map flows * smoothly. Path uses the x and y coordinates from camera view to construct * cells for path finding algorithms. */ public class GameView { // Scene is a helper class to game view. it renders the entire map to memory // for the camera view. Scene scene; // Camera View is a helper class to game view. It clips the Scene into a // small image that follows the players coordinates. CameraView Camera; // Path is a helper class to game view. It observes and calculates the // coordinates of camera view and divides them into Grids/Cells for Path // finding. Path path; // this represents the player and has a getSprite() method that will return // the current frame column row combination of the passed sprite sheet. Sprite player; }

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  • getting a job in game industry as a developer, just knowing a game engine

    - by numerical25
    I recently enrolled at a community college for game developement. But I am skeptical about the circulum. I have no experience in the gaming industry so I wouldnt be able to tell rather its a good investment or not. So I am asking you. I dont want to get too much into detail of all the classes I am taking so I will try to be brief. By the time I graduate, I should have a understanding of how a game engine works. I will be working with the unreal engine to develop a Multiplayer game from scratch. So in the process of my final project, I will learn how to work within the unreal engine, Learn python and learn how to use it's API to connect to a remote server and build game mechanics. Overall I will also recieve a associates degree in game development. I learn c++ but not c. The director said he was trying to implement c in the program as well. What I notice is I will not learn how to build a 3d game engine from scratch. They do not teach any AI. I will not learn how to work with the graphics card using a graphic's api such as DirectX or OpenGL. I know building a game engine from scratch is a little complex, but at the same time the track is requireing me to take some advances math courses such a calculus and geotomtry 1 and 2. I also got to take a physic class. I just think thats a little much for just learning how to use the unreal engine but not actually build one or try to learn the anatomy of a game engine. Is this good enough to possibly land my a job in the insdustry. If I left anything out or was not detail, please feel free to ask more questions. Thanks Guys!!

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  • Music Rhythm Game: Copyright Music Question for Independent (Indie) Game Developers

    - by David Dimalanta
    I have a curious question regarding on musics used in music rhythm game. In Guitar Hero for example, they used all different music albums in one program. Then, each album requires to ask permission to the owner, composer of the music, or the copyright owner of the music. Let's say, if you used 15 albums for the music rhythm game, then you have to contact 15 copyright owners and it might be that, for the game developer, that the profit earned goes to the copyright owner or owner of this music. For the independent game developers, was it okay if either used the copyright music by just mentioning the name of the singer included in the credits and in the music select screen or use the non-popular/old music that about 50 years ago? And, does still earn money for the indie game developers by making free downloadable game?

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  • Game show game engine [closed]

    - by Red
    So, I am pretty new to the world of game development, so I am a bit fuzzy on what I require. Could someone suggest a game engine that I could use? I need it to be light weight (my game won't require that much power) and have networking functionality for multiplay or even an MMO aspect. The game I am making is like a game show, so it is your basic choose and answer hit the buzzer kind of game. Any suggestions? I would also like it to be open source or at the least free. I would like to support open source projects.

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  • Turning a board game idea into a browser based, slow paced gameplay

    - by guillaume31
    Suppose I want to create a strategy game with global mutable state shared between all players (think game board). But unlike a board game, I don't want it to be real time action and/or turn-based. Instead, players should be able to log in at any time of the day and spend a fixed number of action points per day as they wish. As opposed to a few hours, game sessions would run over a few weeks. This is meant to reward good strategy rather than time spent playing (as an alternative, hardcore players could always play multiple games in parallel instead) as well as all kind of issues related to live playing like disconnections and synchronization. The game should remain addictive still have a low time investment footprint for casual players. So far so good, but this still leaves open the question of when to solve actions and when they should be visible. I want to avoid "ninja play" like doing all your moves just a few minutes before daily point reset to take other players by surprise, or people spamming F5 to place a well-timed action which would defeat the whole point of a non real-time game. I thought of a couple of approaches to that : Resolve all events in a single scheduled process running once a day. This basically means a "blind" gameplay where players can take actions but don't see their results immediately. The thing is, I played a similar browser game a few years ago and didn't like the fact that you feel disconnected and powerless until there's that deus ex machina telling you what really happened during all that time. You see the world evolve in large increments of one day, which often doesn't seem like seeing it evolve at all. For actions that have an big impact on the game or on other players (attacks, big achievements), make them visible to everyone immediately but delay their effect by something like 24 hours. Opposing players could be notified when such an event happens, so that they can react to it. Do you have any other ideas how I could go about solving this ? Are there any known approaches in similar existing games ?

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  • How do games like Halo 3 save in-game footage? [duplicate]

    - by CPP_Person
    This question already has an answer here: How to design a replay system 11 answers I was just wondering how games (such as Halo 3, like the title says) save in-game replay? Since it gives the ability to look around at almost every possible angle it can't be a simple recording. What is the logic behind this? Here is a good example of what Halo 3's footage looks like.

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  • SPARC T4-2 Produces World Record Oracle Essbase Aggregate Storage Benchmark Result

    - by Brian
    Significance of Results Oracle's SPARC T4-2 server configured with a Sun Storage F5100 Flash Array and running Oracle Solaris 10 with Oracle Database 11g has achieved exceptional performance for the Oracle Essbase Aggregate Storage Option benchmark. The benchmark has upwards of 1 billion records, 15 dimensions and millions of members. Oracle Essbase is a multi-dimensional online analytical processing (OLAP) server and is well-suited to work well with SPARC T4 servers. The SPARC T4-2 server (2 cpus) running Oracle Essbase 11.1.2.2.100 outperformed the previous published results on Oracle's SPARC Enterprise M5000 server (4 cpus) with Oracle Essbase 11.1.1.3 on Oracle Solaris 10 by 80%, 32% and 2x performance improvement on Data Loading, Default Aggregation and Usage Based Aggregation, respectively. The SPARC T4-2 server with Sun Storage F5100 Flash Array and Oracle Essbase running on Oracle Solaris 10 achieves sub-second query response times for 20,000 users in a 15 dimension database. The SPARC T4-2 server configured with Oracle Essbase was able to aggregate and store values in the database for a 15 dimension cube in 398 minutes with 16 threads and in 484 minutes with 8 threads. The Sun Storage F5100 Flash Array provides more than a 20% improvement out-of-the-box compared to a mid-size fiber channel disk array for default aggregation and user-based aggregation. The Sun Storage F5100 Flash Array with Oracle Essbase provides the best combination for large Oracle Essbase databases leveraging Oracle Solaris ZFS and taking advantage of high bandwidth for faster load and aggregation. Oracle Fusion Middleware provides a family of complete, integrated, hot pluggable and best-of-breed products known for enabling enterprise customers to create and run agile and intelligent business applications. Oracle Essbase's performance demonstrates why so many customers rely on Oracle Fusion Middleware as their foundation for innovation. Performance Landscape System Data Size(millions of items) Database Load(minutes) Default Aggregation(minutes) Usage Based Aggregation(minutes) SPARC T4-2, 2 x SPARC T4 2.85 GHz 1000 149 398* 55 Sun M5000, 4 x SPARC64 VII 2.53 GHz 1000 269 526 115 Sun M5000, 4 x SPARC64 VII 2.4 GHz 400 120 448 18 * – 398 mins with CALCPARALLEL set to 16; 484 mins with CALCPARALLEL threads set to 8 Configuration Summary Hardware Configuration: 1 x SPARC T4-2 2 x 2.85 GHz SPARC T4 processors 128 GB memory 2 x 300 GB 10000 RPM SAS internal disks Storage Configuration: 1 x Sun Storage F5100 Flash Array 40 x 24 GB flash modules SAS HBA with 2 SAS channels Data Storage Scheme Striped - RAID 0 Oracle Solaris ZFS Software Configuration: Oracle Solaris 10 8/11 Installer V 11.1.2.2.100 Oracle Essbase Client v 11.1.2.2.100 Oracle Essbase v 11.1.2.2.100 Oracle Essbase Administration services 64-bit Oracle Database 11g Release 2 (11.2.0.3) HP's Mercury Interactive QuickTest Professional 9.5.0 Benchmark Description The objective of the Oracle Essbase Aggregate Storage Option benchmark is to showcase the ability of Oracle Essbase to scale in terms of user population and data volume for large enterprise deployments. Typical administrative and end-user operations for OLAP applications were simulated to produce benchmark results. The benchmark test results include: Database Load: Time elapsed to build a database including outline and data load. Default Aggregation: Time elapsed to build aggregation. User Based Aggregation: Time elapsed of the aggregate views proposed as a result of tracked retrieval queries. Summary of the data used for this benchmark: 40 flat files, each of size 1.2 GB, 49.4 GB in total 10 million rows per file, 1 billion rows total 28 columns of data per row Database outline has 15 dimensions (five of them are attribute dimensions) Customer dimension has 13.3 million members 3 rule files Key Points and Best Practices The Sun Storage F5100 Flash Array has been used to accelerate the application performance. Setting data load threads (DLTHREADSPREPARE) to 64 and Load Buffer to 6 improved dataloading by about 9%. Factors influencing aggregation materialization performance are "Aggregate Storage Cache" and "Number of Threads" (CALCPARALLEL) for parallel view materialization. The optimal values for this workload on the SPARC T4-2 server were: Aggregate Storage Cache: 32 GB CALCPARALLEL: 16   See Also Oracle Essbase Aggregate Storage Option Benchmark on Oracle's SPARC T4-2 Server oracle.com Oracle Essbase oracle.com OTN SPARC T4-2 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 28 August 2012.

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  • World Record Siebel PSPP Benchmark on SPARC T4 Servers

    - by Brian
    Oracle's SPARC T4 servers set a new World Record for Oracle's Siebel Platform Sizing and Performance Program (PSPP) benchmark suite. The result used Oracle's Siebel Customer Relationship Management (CRM) Industry Applications Release 8.1.1.4 and Oracle Database 11g Release 2 running Oracle Solaris on three SPARC T4-2 and two SPARC T4-1 servers. The SPARC T4 servers running the Siebel PSPP 8.1.1.4 workload which includes Siebel Call Center and Order Management System demonstrates impressive throughput performance of the SPARC T4 processor by achieving 29,000 users. This is the first Siebel PSPP 8.1.1.4 benchmark supporting 29,000 concurrent users with a rate of 239,748 Business Transactions/hour. The benchmark demonstrates vertical and horizontal scalability of Siebel CRM Release 8.1.1.4 on SPARC T4 servers. Performance Landscape Systems Txn/hr Users Call Center Order Management Response Times (sec) 1 x SPARC T4-1 (1 x SPARC T4 2.85 GHz) – Web 3 x SPARC T4-2 (2 x SPARC T4 2.85 GHz) – App/Gateway 1 x SPARC T4-1 (1 x SPARC T4 2.85 GHz) – DB 239,748 29,000 0.165 0.925 Oracle: Call Center + Order Management Transactions: 197,128 + 42,620 Users: 20300 + 8700 Configuration Summary Web Server Configuration: 1 x SPARC T4-1 server 1 x SPARC T4 processor, 2.85 GHz 128 GB memory Oracle Solaris 10 8/11 iPlanet Web Server 7 Application Server Configuration: 3 x SPARC T4-2 servers, each with 2 x SPARC T4 processor, 2.85 GHz 256 GB memory 3 x 300 GB SAS internal disks Oracle Solaris 10 8/11 Siebel CRM 8.1.1.5 SIA Database Server Configuration: 1 x SPARC T4-1 server 1 x SPARC T4 processor, 2.85 GHz 128 GB memory Oracle Solaris 11 11/11 Oracle Database 11g Release 2 (11.2.0.2) Storage Configuration: 1 x Sun Storage F5100 Flash Array 80 x 24 GB flash modules Benchmark Description Siebel 8.1 PSPP benchmark includes Call Center and Order Management: Siebel Financial Services Call Center – Provides the most complete solution for sales and service, allowing customer service and telesales representatives to provide superior customer support, improve customer loyalty, and increase revenues through cross-selling and up-selling. High-level description of the use cases tested: Incoming Call Creates Opportunity, Quote and Order and Incoming Call Creates Service Request . Three complex business transactions are executed simultaneously for specific number of concurrent users. The ratios of these 3 scenarios were 30%, 40%, 30% respectively, which together were totaling 70% of all transactions simulated in this benchmark. Between each user operation and the next one, the think time averaged approximately 10, 13, and 35 seconds respectively. Siebel Order Management – Oracle's Siebel Order Management allows employees such as salespeople and call center agents to create and manage quotes and orders through their entire life cycle. Siebel Order Management can be tightly integrated with back-office applications allowing users to perform tasks such as checking credit, confirming availability, and monitoring the fulfillment process. High-level description of the use cases tested: Order & Order Items Creation and Order Updates. Two complex Order Management transactions were executed simultaneously for specific number of concurrent users concurrently with aforementioned three Call Center scenarios above. The ratio of these 2 scenarios was 50% each, which together were totaling 30% of all transactions simulated in this benchmark. Between each user operation and the next one, the think time averaged approximately 20 and 67 seconds respectively. Key Points and Best Practices No processor cores or cache were activated or deactivated on the SPARC T-Series systems to achieve special benchmark effects. See Also Siebel White Papers SPARC T4-1 Server oracle.com OTN SPARC T4-2 Server oracle.com OTN Siebel CRM oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 30 September 2012.

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  • Issue with TurnBased Multiplayer Game in Game-kit

    - by Nirav
    I am working with cocos2d game in which i am implementing Game-kit. My game supports multiplayer option. Actually as given example Raywenderlich link. I am GKTurnBasedMultiplayer class from Game-kit. But now the issue when first player connected to game center and will select option of "Play Now" it automatches for another player. but issue is it directly connects and starts the match, and doesn't wait for another player. I am using [[GCTurnBasedMatchHelper sharedInstance] findMatchWithMinPlayers:2 maxPlayers:4 viewController:viewConroller]; for connecting and playing with other players but directly connects the match. I want to wait for another player. That is the issue. I am also using GCTurnBasedMatchHelper Class.

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  • Good Open souce game engines for making MMO game

    - by Call Me Dummy
    I am interested in making a MMO game but I am not sure where to start. I am looking for an open source game engine which is simple to use and allows me to concentrate on the game design and architecture. I have some basic C,C++,C# knowledge. After lots of searching in google I was going to start out with Ogre3D but soon realized that it is a rendering engine and does not include physics engine. I have not tried it yet since in many forums it says they don't have a good documentation. So is there any good open source game engine good for fast game developing ? Some key features I want include basic requirements like collision detection, object to object collision detection, physics etc.

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  • Unity 3D game idea for a fun and teaching game

    - by rasheeda
    I have been brainstorming for months now on writing a unity 3D game for my final year computer science project. I have been learning unity for sometime now but comming up with a concept is quite difficult than i thought. The game has to be really fun and also educational, one that the school and community can benefit from. I am thinking about a third person game. where the player runs round in an enviroment, picks up coins and earn points. This alone wouldn't earn me points and I have been trying to find new ideas of my own and all over the net but to no avail. Hopefully you guys can help me out with an idea, and how to make the lecturers appreciate the game and also make kids wanna play play it for a reason. Thanks.

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  • Multiplayer card game using PHP/Ajax and mysql

    - by Alireza Seifi
    I am designing a map game, using PHP and MYSQL. I don't know how to make the players who sign-in to the website to see other players who are also connected to the site and be able to chat with one another. I want to design the game in such a way that 2 players can play with each other and be able to send messages during the game while others groups are playing at the same time. I have designed the map game successfully, but the problem is making the player 1 who log-in to site to see the player 2 who will also log-in and both can get connected to play each other. http://i.stack.imgur.com/YyCPG.png I will appreciate your responses.

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  • Do game-theoretic considerations stand in the way of this market-based game-mechanic achieving its goals?

    - by BerndBrot
    Mechanic The mechanic is called "market manipulation" and is supposed to work like this: Players can enter the London Stock Exchange (LSE) LSE displays the stock prices of 8 to 10 companies and derivatives. This number is relatively small to ensure that players will collide in their efforts to manipulate the market in their favor. The prices are calculated based on real world prices of these companies and derivatives (in real time) any market manipulations that were conducted by the players any market corrections of the system Players can buy and sell shares with cash, a resource in the game, at current in-game market value Players can manipulate the market, i.e. let the price of a share either rise or fall, by some amount, over a certain period of time. Manipulating the market requires spending certain in-game resources and is therefore limited. The system continuously corrects market manipulations by letting the in-game prices converge towards their real world counterparts at a rate of 2% of the difference between the two per hour. Because of this market correction mechanism, pushing up prices (and screwing down prices) becomes increasingly difficult the higher (lower) the price already is. Goals Players are supposed to collide (and have incentives to collide) in their efforts to manipulate the market in their favor, especially when it comes to manipulation efforts by different groups. Prices should not resolve around any equilibrium points. The more variance the better. Band-wagoning should always involve risk (recognizing that prices start rising should not be a sure sign that they will keep rising so that everybody can make easy profits even when they don't manipulate the market themselves) Question Are there any game-theoretic considerations that prevent the mechanic from achieving these goals?

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  • What makes a game a game vs something else like a puzzle or a toy?

    - by Shannon John Clark
    Famously the Sims and similar games have been described by some designers as Toys and not "really" games. I'm curious if there is a good answer to what makes something a game. For example many companies sell Sudoku games - EA has an iPhone one, IronSudoku offers a great web based one, and there are countless others on most platforms. Many newspapers publish Sudoku puzzles in their print editions and often online. What differentiates a game from a puzzle? (or are all Sudoku "games" misnamed?) I'm not convinced there is a simple or easy answer - but I'd love to be proven wrong. I've seen some definitions and emphasize "rules" as core to something being a game (vs. "real life") but puzzles have rules as well - as do many other things. I'm open to answers that either focus only on computer games (on any platform) or which expand to include games and gameplay across many platforms. Here to I'm not fully convinced the lines are clear - is a "game" of D&D played over a virtual tabletop with computer dice rollers, video & audio chat a computer game or something else? (I'd lean towards something else - but where do you draw that line?)

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