Presentation of one of my projects on computer graphics. It talks about Volume Rendering of Unstructured Tetrahedral Grids using Intel / nVidia OpenCL.
Presentation by Rose Valley Elementary School, Kelowna, BC.
(Mr Bradshaw's 6th Grade Class)
Inspired by The Ambeciles route for the 2010 Mongol Rally.
http://www.theambeciles.com/
Optimizing Set-Similarity Join and Search with Different Prefix SchemesHPCC Systems
As part of the 2018 HPCC Systems Summit Community Day event:
Up first, Zhe Yu, NC State University briefly discusses his poster, How to Be Rich: A Study of Monsters and Mice of American Industry
Following, Fabian Fier, presents his breakout session in the Documentation & Training Track.
Finding duplicate textual content is crucial for many applications, especially plagiarism detection. When dealing with millions of documents finding duplicate content becomes very time-consuming. Thus it needs scalable and efficient data structures and algorithms that solve this task in seconds rather than hours. In my talk, I present an optimization of a common filter-and-verification set-similarity join and search approach. Filter-and-verification means that we only consider such pairs of objects which share a common word or token in a prefix. Such pairs are potentially similar and are verified in a subsequent step. The candidate set is usually orders of magnitudes smaller than the cross product over an input set. We optimizied this approach by regarding overlaps larger than 1, which reduces the candidate set further and makes the verification faster. On the other hand this requires larger prefixes, which use more memory. Our experiments using HPCC Systems show that we can usually optimize the runtime by choosing an overlap different from the standard overlap 1.
Fabian Fier is a PhD student at the database research group of Johann-Christoph Freytag. He holds a diploma in computer science from Humboldt-Universität. His research interest is similarity search on web-scale data. He uses techniques from textual similarity joins on Big Data and adapts them to similiarity search.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Presentation by Rose Valley Elementary School, Kelowna, BC.
(Mr Bradshaw's 6th Grade Class)
Inspired by The Ambeciles route for the 2010 Mongol Rally.
http://www.theambeciles.com/
Optimizing Set-Similarity Join and Search with Different Prefix SchemesHPCC Systems
As part of the 2018 HPCC Systems Summit Community Day event:
Up first, Zhe Yu, NC State University briefly discusses his poster, How to Be Rich: A Study of Monsters and Mice of American Industry
Following, Fabian Fier, presents his breakout session in the Documentation & Training Track.
Finding duplicate textual content is crucial for many applications, especially plagiarism detection. When dealing with millions of documents finding duplicate content becomes very time-consuming. Thus it needs scalable and efficient data structures and algorithms that solve this task in seconds rather than hours. In my talk, I present an optimization of a common filter-and-verification set-similarity join and search approach. Filter-and-verification means that we only consider such pairs of objects which share a common word or token in a prefix. Such pairs are potentially similar and are verified in a subsequent step. The candidate set is usually orders of magnitudes smaller than the cross product over an input set. We optimizied this approach by regarding overlaps larger than 1, which reduces the candidate set further and makes the verification faster. On the other hand this requires larger prefixes, which use more memory. Our experiments using HPCC Systems show that we can usually optimize the runtime by choosing an overlap different from the standard overlap 1.
Fabian Fier is a PhD student at the database research group of Johann-Christoph Freytag. He holds a diploma in computer science from Humboldt-Universität. His research interest is similarity search on web-scale data. He uses techniques from textual similarity joins on Big Data and adapts them to similiarity search.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
발표자: 송환준(KAIST 박사과정)
발표일: 2018.8.
(Parallel Clustering Algorithm Optimization for Large-Scale Data Analytics)
Clustering은 데이터 분석에 가장 널리 쓰이는 방법 중 하나로 주어진 데이터를 유사성에 기초하여 여러 개의 그룹으로 나누는 작업이다. 하지만 Clustering 방법의 높은 계산 복잡도 때문에 대용량 데이터 분석에는 잘 사용되지 못하고 있다. 최근 이 높은 복잡도 문제를 해결하기 위해 많은 연구가 Hadoop, Spark와 같은 분산 컴퓨팅 방식을 적용하고 있지만 기존 Clustering 알고리즘을 분산 환경에 최적화시키는 것은 쉽지 않다. 특히, 효율성을 높이기 위해 정확성을 손실하는 문제 그리고 여러 작업자들 간의 부하 불균형 문제는 알고리즘을 분산처리 할 때 발생하는 대표적인 문제이다. 본 세미나에서는 대표적 Clustering 알고리즘인 DBSCAN을 분산처리 할 때 발생하는 여러 도전 과제에 초점을 맞추고 이를 해결 할 수 있는 새로운 해결책을 제시한다. 실제로 이 방법은 최신 연구의 방법과 비교하여 정확도 손실 없이 최대 180배까지 알고리즘의 성능을 향상시켰다.
본 세미나는 SIGMOD 2018에서 발표한 다음 논문에 대한 내용이다.
Song, H. and Lee, J., "RP-DBSCAN: A Superfast Parallel DBSCAN Algorithm Based on Random Partitioning," In Proc. 2018 ACM Int'l Conf. on Management of Data (SIGMOD), Houston, Texas, pp. 1173 ~ 1187, June 2018
1. Background
- Concept of Clustering
- Concept of Distributed Processing (MapReduce)
- Clustering Algorithms (Focus on DBSCAN)
2. Challenges of Parallel Clustering
- Parallelization of Clustering Algorithm (Focus on DBSCAN)
- Existing Work
- Challenges
3. Our Approach
- Key Idea and Key Contribution
- Overview of Random Partitioning-DBSCAN
4. Experimental Results
5. Conclusions
AI optimizing HPC simulations (presentation from 6th EULAG Workshop)byteLAKE
See our presentation from the 6th International EULAG Users Workshop. We talked about taking HPC to the "Industry 4.0" by implementing smart techniques to optimize the codes in terms of performance and energy consumption. It explains how Machine Learning can dynamically optimize HPC simulations and byteLAKE's software autotuning solution.
Find out more about byteLAKE at: www.byteLAKE.com
Efficient Variable Size Template Matching Using Fast Normalized Cross Correla...Gurbinder Gill
In this presentation we propose the parallel implementation of template matching using Full Search using NCC as a measure using the concept of pre-computed sum-tables referred to as FNCC for high resolution images on NVIDIA’s Graphics Processing Units (GP-GPU’s)
This talk is given at AITAM, Tekkali. I have introduced developments in multi-core computers along with their architectural developments. Also, I have explained about high performance computing, where these are used. Also, I have introduced to OpenMP fundamentals with live practice sessions.
Data Analytics and Simulation in Parallel with MATLAB*Intel® Software
This talk covers the current parallel capabilities in MATLAB*. Learn about its parallel language and distributed and tall arrays. Interact with GPUs both on the desktop and in the cluster. Combine this information into an interesting algorithmic framework for data analysis and simulation.
Cost Estimation in Project Management - Case of Solar Assisted Water PumpNitesh Bhatia
Presentation on steps taken for coming out with effective cost estimation in any project. As case study one of the project done on Solar Assisted Water Pump has been taken for cost estimation.
More Related Content
Similar to Volume Rendering of Unstructured Tetrahedral Grids using Intel / nVidia OpenCL
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
발표자: 송환준(KAIST 박사과정)
발표일: 2018.8.
(Parallel Clustering Algorithm Optimization for Large-Scale Data Analytics)
Clustering은 데이터 분석에 가장 널리 쓰이는 방법 중 하나로 주어진 데이터를 유사성에 기초하여 여러 개의 그룹으로 나누는 작업이다. 하지만 Clustering 방법의 높은 계산 복잡도 때문에 대용량 데이터 분석에는 잘 사용되지 못하고 있다. 최근 이 높은 복잡도 문제를 해결하기 위해 많은 연구가 Hadoop, Spark와 같은 분산 컴퓨팅 방식을 적용하고 있지만 기존 Clustering 알고리즘을 분산 환경에 최적화시키는 것은 쉽지 않다. 특히, 효율성을 높이기 위해 정확성을 손실하는 문제 그리고 여러 작업자들 간의 부하 불균형 문제는 알고리즘을 분산처리 할 때 발생하는 대표적인 문제이다. 본 세미나에서는 대표적 Clustering 알고리즘인 DBSCAN을 분산처리 할 때 발생하는 여러 도전 과제에 초점을 맞추고 이를 해결 할 수 있는 새로운 해결책을 제시한다. 실제로 이 방법은 최신 연구의 방법과 비교하여 정확도 손실 없이 최대 180배까지 알고리즘의 성능을 향상시켰다.
본 세미나는 SIGMOD 2018에서 발표한 다음 논문에 대한 내용이다.
Song, H. and Lee, J., "RP-DBSCAN: A Superfast Parallel DBSCAN Algorithm Based on Random Partitioning," In Proc. 2018 ACM Int'l Conf. on Management of Data (SIGMOD), Houston, Texas, pp. 1173 ~ 1187, June 2018
1. Background
- Concept of Clustering
- Concept of Distributed Processing (MapReduce)
- Clustering Algorithms (Focus on DBSCAN)
2. Challenges of Parallel Clustering
- Parallelization of Clustering Algorithm (Focus on DBSCAN)
- Existing Work
- Challenges
3. Our Approach
- Key Idea and Key Contribution
- Overview of Random Partitioning-DBSCAN
4. Experimental Results
5. Conclusions
AI optimizing HPC simulations (presentation from 6th EULAG Workshop)byteLAKE
See our presentation from the 6th International EULAG Users Workshop. We talked about taking HPC to the "Industry 4.0" by implementing smart techniques to optimize the codes in terms of performance and energy consumption. It explains how Machine Learning can dynamically optimize HPC simulations and byteLAKE's software autotuning solution.
Find out more about byteLAKE at: www.byteLAKE.com
Efficient Variable Size Template Matching Using Fast Normalized Cross Correla...Gurbinder Gill
In this presentation we propose the parallel implementation of template matching using Full Search using NCC as a measure using the concept of pre-computed sum-tables referred to as FNCC for high resolution images on NVIDIA’s Graphics Processing Units (GP-GPU’s)
This talk is given at AITAM, Tekkali. I have introduced developments in multi-core computers along with their architectural developments. Also, I have explained about high performance computing, where these are used. Also, I have introduced to OpenMP fundamentals with live practice sessions.
Data Analytics and Simulation in Parallel with MATLAB*Intel® Software
This talk covers the current parallel capabilities in MATLAB*. Learn about its parallel language and distributed and tall arrays. Interact with GPUs both on the desktop and in the cluster. Combine this information into an interesting algorithmic framework for data analysis and simulation.
Cost Estimation in Project Management - Case of Solar Assisted Water PumpNitesh Bhatia
Presentation on steps taken for coming out with effective cost estimation in any project. As case study one of the project done on Solar Assisted Water Pump has been taken for cost estimation.
Mapping - Reality and Virtual Reality (Strictly No AR!!)Nitesh Bhatia
A small project done at Virtual Reality Lab at CPDM, IISc. The PPT talks about an idea of mapping Reality and Virtual Reality using electromagnetic position trackers and 3D head mounted display. This project is pure Virtual Reality based implementation and is not dependent on camera based Augmented Reality techniques.
Natural User Interface Demo based on - 3D Brick Game using KinectNitesh Bhatia
Slides on my presentation on Natural User Interface Demo based on - 3D Brick Game using Kinect. In the end you can see youtuve video showing demo of application.
Welocme to ViralQR, your best QR code generator.ViralQR
Welcome to ViralQR, your best QR code generator available on the market!
At ViralQR, we design static and dynamic QR codes. Our mission is to make business operations easier and customer engagement more powerful through the use of QR technology. Be it a small-scale business or a huge enterprise, our easy-to-use platform provides multiple choices that can be tailored according to your company's branding and marketing strategies.
Our Vision
We are here to make the process of creating QR codes easy and smooth, thus enhancing customer interaction and making business more fluid. We very strongly believe in the ability of QR codes to change the world for businesses in their interaction with customers and are set on making that technology accessible and usable far and wide.
Our Achievements
Ever since its inception, we have successfully served many clients by offering QR codes in their marketing, service delivery, and collection of feedback across various industries. Our platform has been recognized for its ease of use and amazing features, which helped a business to make QR codes.
Our Services
At ViralQR, here is a comprehensive suite of services that caters to your very needs:
Static QR Codes: Create free static QR codes. These QR codes are able to store significant information such as URLs, vCards, plain text, emails and SMS, Wi-Fi credentials, and Bitcoin addresses.
Dynamic QR codes: These also have all the advanced features but are subscription-based. They can directly link to PDF files, images, micro-landing pages, social accounts, review forms, business pages, and applications. In addition, they can be branded with CTAs, frames, patterns, colors, and logos to enhance your branding.
Pricing and Packages
Additionally, there is a 14-day free offer to ViralQR, which is an exceptional opportunity for new users to take a feel of this platform. One can easily subscribe from there and experience the full dynamic of using QR codes. The subscription plans are not only meant for business; they are priced very flexibly so that literally every business could afford to benefit from our service.
Why choose us?
ViralQR will provide services for marketing, advertising, catering, retail, and the like. The QR codes can be posted on fliers, packaging, merchandise, and banners, as well as to substitute for cash and cards in a restaurant or coffee shop. With QR codes integrated into your business, improve customer engagement and streamline operations.
Comprehensive Analytics
Subscribers of ViralQR receive detailed analytics and tracking tools in light of having a view of the core values of QR code performance. Our analytics dashboard shows aggregate views and unique views, as well as detailed information about each impression, including time, device, browser, and estimated location by city and country.
So, thank you for choosing ViralQR; we have an offer of nothing but the best in terms of QR code services to meet business diversity!
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
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The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
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GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
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https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
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Attacks on counties – USA
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In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
3. Introduction: Volume Rendering
• Volume rendering is a technique that can
be used to visualize sampled 3D scalar
data as a continuous medium or extract
features.
Most algorithms for direct volume rendering
have assumed structured data in form of
rectilinear grid.
• In this project we worked on a method for
rendering unstructured volume; volume
represented by group of tetrahedrals.
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3
4. Problem Formulation
• The idea is to convert unstructured input tetrahedral grid
(UG) to output structured regular grid (SG) and render it
using existing ray casting system.
• The data represented in UG must be interpolated to
produce SG.
• The UG consists of tetrahedrals bounded by four vertices
numbered 1,2,3,4, the coordinates of ith vertex being (xi,
yi, zi) and associated data value is denoted fi.
• The data values are assumed to be the values of an
unknown locally smooth trivariate function
interpolate discussed in next heading.
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1/3
5. Problem Formulation
• Let P = (x,y,z) be the point at which the value of interpolation function is
to be estimated.
Two different interpolation schemes are followed here:
• Scheme 1: Map SG to UG
• For a given point P of SG and find the tetrahedral associated with P
in UG
• Estimate the function values for given cell based on interpolate.
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empty SG UG SG
2/3
6. Problem Formulation
• Scheme 2: Map UG to SG
• Take a tetrahedral from UG and find points Ps lying on SG
• Estimate the function value at Ps based on interpolate.
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UG empty SG SG
3/3
7. Tetrahedral Interpolation: interpolate
• Given a tetrahedron T with vertices v1, v2, v3, v4 and
function value associated with these vertices be f1, f2, f3
and f4, the problem is to find interpolated function value f
for any given point P.
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.P(f)
v1(f1)
v2(f2)v4(f4)
v3(f3)
1/4
8. Tetrahedral Interpolation: interpolate
Geometric Solution
• Take ratio of perpendicular distance of P
to a face with perpendicular distance of
opposite vertex to that face.
• Find these ratios with all four faces and
name them l1, l2, l3 and l4.
• If the point P is lying inside tetrahedral
these ratios will come between 0 and 1.
• Sum of these ratios will always be 1.
• These l1,l2, l3 and l4 are known as
barycentric coordinates of point P with
respect to tetrahedral T.
• f = l1*f1 + l2*f2 + l3*f3 + l4*f4
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11. Implementation
In implementation we are following 3 step approach
1. Load the vertices and tetrahedron information from
given .ts file into CPU memory
2. Based on two schemes presented, perform
computations using OpenCL (or OpenMP) to form a
regular grid
3. Display the grid by Ray Casting in OpenCL using CL-GL
Interoperability.
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12. Implementation: Description
Step1:
• The data set given .ts file is form of list of vertices with 3D
coordinates and associated function value and then a list of
tetrahedrons with asociated 4 vertices.
• We are first loading this information into memory.
• While loading the vertices we are computing minimum and
maximum values for (x,y,z) coordinates and storing it as minX,
minY, minZ, maxX, maxY, maxZ.
• We are then finding the difference between these minimum and
maximum values and storing it as diffX, diffY, diffZ.
• We are then computing diff equal to maximum of diffX, diffY
and diffZ.
• We are then finding dimensions of our bounding box with side
equal to diff.
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13. Step 2:
• Given
• We are computing A-1 for each tetrahedron
• We define a constant STEP_SIZE = 128 (or any other
value) which gives dimension of our volume as
128*128*128.
• We are setting the resolution (step size) of our volume as
res = diff / STEP_SIZE
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14. Scheme 1:
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1. Finding point lying
on SG
2. searching for
associated T in UG
and finding f value
using interpolation
15. • This scheme is implemented in both OpenCL and
OpenMP
• In OpenMP implementation we are adding following two
lines as compiler directive in starting of loop:
• #paragma omp set_num_threads(8)
• #paragma omp parallel for shared(i,j,k)
• In OpenCL implementation we are setting our dimensions
as 1D with
• size_t global_size = {STEP_SIZE * STEP_SIZE * STEP_SIZE}
• Here we are Parallelizing in terms of volume element
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16. Scheme2:
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1. Finding limits of
points lying inside
tetrahedral
2. For given limits finding f
values of points associated
with SG
17. • Scheme 2 is implemented in OpenCL. We are setting our
dimensions as 1D with
size_t global_size = tet_qty
• Here we are Parallelizing in terms of tetrahedral quantity
Step 3:
• We are then giving this 1D grid of function values to
existing ray tracer (provided by nVidia in their SDK) as
input.
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18. Results
• Hardware / Software for tests
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GPU
Model: nVidia Quadro FX 580
Cores: 32
Core Clock: 450 MHz
Memory: 512MB
Memory Bandwidth: 25.6 GiB/s
CPU
Model: Intel Core i7 860
Cores / Threads: 4/8
Clock Speed: 2.8GHz (3.0GHz when running on full load)
Memory: 8 GB
Memory Bandwidth: 21GB/s
OS / SDKs
Microsoft Windows 7 Professional 64Bit
Visual Studio 2010 32Bit
Microsoft OpenMP
nVidia CUDA SDK 3.2
nVidia OpenCL 1.1
Intel OpenCL 1.1 alpha
Input UG
Torus1.ts
Torusf1.ts
Torus8.ts
Engine.ts
24. Impressions
• Learning OpenCL was a challenging task but we it was
interesting.
• Debugging OpenCL is difficult task as stream output
(“printf” function) cannot be called in openCL kernel. In
Intel’s compiler is based on OpenCL 1.1 in which “printf” is
supported.
• Double precision computations are not supported on my
card.
• Graphic Driver Crash Problem
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25. “We now know a thousand ways not to
build a light bulb”
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THANKS !