Book Review: Parallel Algorithms

By John E. West

April 27, 2009

Parallel Algorithms by Henri Casanova, Arnaud Legrand, and Yves Robert (CRC Press, 2009) is a text meant for those with a desire to understand the theoretical underpinnings of parallelism from a computer science perspective. As the authors themselves point out, this is not a high performance computing book — there is no real attention given to HPC architectures or practical scientific computing. You also won’t leave this book a competent parallel programmer ready to implement an application. But you will have the tools you need to continue on a rigorous research track into the computer science aspects of parallel computing.

The preface describes the text as aimed at graduate students and postgraduate researchers in computer science, and this is dead on. The book is very general, and very theoretical, with proofs, theorems, lemmas, complexity analysis, and the whole nine yards. In the quest to maintain generality and build a theoretical framework for understanding research aspects of parallel algorithms, you don’t get much further than matrix-matrix multiplication and basic stencil computation in terms of practical discussion of algorithms. Each chapter includes a thorough problem set that extends the topics covered in the chapter; solutions are provided for select problems.

The book is organized into three sections: models, parallel algorithms, and scheduling. The models section begins with (chapters 1-2) coverage of classic theoretical models of computing in parallel, PRAM and sorting networks. Chapter 3 is about the models of communications networks needed to reason about the complexity and general effectiveness of algorithms when implemented on specific hardware. This chapter talks about topologies like cliques, rings, grids, and variants of the torus and hypercube, and also touches on models for peer-to-peer computing networks.

Chapters 4 and 5 discuss parallel algorithms on rings and grids of processors. The algorithmic discussion is a foundation upon which to develop the theoretical tools for reasoning about the performance and complexity of parallel algorithms in general. These chapters are not meant to be useful implementation guides for those developing applications. The authors examine matrix-vector and matrix-matrix multiplication as well as basic stencil computations and LU factorization. Basic data distribution patterns are also discussed (block, cyclic, etc.), and are used in conjunction with an analysis of the algorithms in the context of the communication network models to understand the theoretical performance advantages and general relevance of data distribution to effective parallel computation. These sections of chapters 4 and 5 establish theoretical foundations for some of the rules of thumb we have in HPC, explaining why they work, and they are used to establish some generalities about the virtues and vices of some of the topologies with respect to one another.

The remaining chapters are about workload management. Chapter 6 addresses load balancing within an application running on a heterogenous platform, e.g., a cluster with some fast and some slow(er) processors. The chapter builds the fundamental discussion based on one-dimensional data distributions for which there are accessible solutions and examines those in the context of stencil computations and LU factorization. Then the authors address the difficulties with balancing load in two-dimensional data distributions. Chapters 7 and 8 address task graph scheduling algorithms. Chapter 7 addresses the fundamentals and provides the definitions and theorems needed to prove characteristics of task graph scheduling approaches. Chapter 8 advances this discussion and addresses scheduling of divisible load applications, throughput optimization for master-worker applications in steady-state, scheduling of independent tasks, and loop nest scheduling.

Parallel Algorithms is a book you study, not a book you read. Those well past their CS finals or long out of the research aspects of computer science may find portions of the discussion inaccessible. But those motivated to work through the text will be rewarded with a solid foundation for the study of parallel algorithms.

Parallel Algorithms (Chapman & Hall/Crc Numerical Analy & Scient Comp. Series)

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

HPC Iron, Soft, Data, People – It Takes an Ecosystem!

December 11, 2017

Cutting edge advanced computing hardware (aka big iron) does not stand by itself. These computers are the pinnacle of a myriad of technologies that must be carefully woven together by people to create the computational c Read more…

By Alex R. Larzelere

IBM Begins Power9 Rollout with Backing from DOE, Google

December 6, 2017

After over a year of buildup, IBM is unveiling its first Power9 system based on the same architecture as the Department of Energy CORAL supercomputers, Summit and Sierra. The new AC922 server pairs two Power9 CPUs with f Read more…

By Tiffany Trader

PEZY President Arrested, Charged with Fraud

December 6, 2017

The head of Japanese supercomputing firm PEZY Computing was arrested Tuesday on suspicion of defrauding a government institution of 431 million yen (~$3.8 million). According to reports in the Japanese press, PEZY founde Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Explore the Origins of Space with COSMOS and Memory-Driven Computing

From the formation of black holes to the origins of space, data is the key to unlocking the secrets of the early universe. Read more…

Azure Debuts AMD EPYC Instances for Storage Optimized Workloads

December 5, 2017

AMD’s return to the data center received a boost today when Microsoft Azure announced introduction of instances based on AMD’s EPYC microprocessors. The new instances – Lv2-Series of Virtual Machine – use the EPY Read more…

By John Russell

HPC Iron, Soft, Data, People – It Takes an Ecosystem!

December 11, 2017

Cutting edge advanced computing hardware (aka big iron) does not stand by itself. These computers are the pinnacle of a myriad of technologies that must be care Read more…

By Alex R. Larzelere

IBM Begins Power9 Rollout with Backing from DOE, Google

December 6, 2017

After over a year of buildup, IBM is unveiling its first Power9 system based on the same architecture as the Department of Energy CORAL supercomputers, Summit a Read more…

By Tiffany Trader

Microsoft Spins Cycle Computing into Core Azure Product

December 5, 2017

Last August, cloud giant Microsoft acquired HPC cloud orchestration pioneer Cycle Computing. Since then the focus has been on integrating Cycle’s organization Read more…

By John Russell

GlobalFoundries, Ayar Labs Team Up to Commercialize Optical I/O

December 4, 2017

GlobalFoundries (GF) and Ayar Labs, a startup focused on using light, instead of electricity, to transfer data between chips, today announced they've entered in Read more…

By Tiffany Trader

HPE In-Memory Platform Comes to COSMOS

November 30, 2017

Hewlett Packard Enterprise is on a mission to accelerate space research. In August, it sent the first commercial-off-the-shelf HPC system into space for testing Read more…

By Tiffany Trader

SC17 Cluster Competition: Who Won and Why? Results Analyzed and Over-Analyzed

November 28, 2017

Everyone by now knows that Nanyang Technological University of Singapore (NTU) took home the highest LINPACK Award and the Overall Championship from the recently concluded SC17 Student Cluster Competition. We also already know how the teams did in the Highest LINPACK and Highest HPCG competitions, with Nanyang grabbing bragging rights for both benchmarks. Read more…

By Dan Olds

Perspective: What Really Happened at SC17?

November 22, 2017

SC is over. Now comes the myriad of follow-ups. Inboxes are filled with templated emails from vendors and other exhibitors hoping to win a place in the post-SC thinking of booth visitors. Attendees of tutorials, workshops and other technical sessions will be inundated with requests for feedback. Read more…

By Andrew Jones

SC Bids Farewell to Denver, Heads to Dallas for 30th Anniversary

November 17, 2017

After a jam-packed four-day expo and intensive six-day technical program, SC17 has wrapped up another successful event that brought together nearly 13,000 visit Read more…

By Tiffany Trader

US Coalesces Plans for First Exascale Supercomputer: Aurora in 2021

September 27, 2017

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, in Arlington, Va., yesterday (Sept. 26), it was revealed that the "Aurora" supercompute Read more…

By Tiffany Trader

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

By Rob Farber

Oracle Layoffs Reportedly Hit SPARC and Solaris Hard

September 7, 2017

Oracle’s latest layoffs have many wondering if this is the end of the line for the SPARC processor and Solaris OS development. As reported by multiple sources Read more…

By John Russell

AMD Showcases Growing Portfolio of EPYC and Radeon-based Systems at SC17

November 13, 2017

AMD’s charge back into HPC and the datacenter is on full display at SC17. Having launched the EPYC processor line in June along with its MI25 GPU the focus he Read more…

By John Russell

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Japan Unveils Quantum Neural Network

November 22, 2017

The U.S. and China are leading the race toward productive quantum computing, but it's early enough that ultimate leadership is still something of an open questi Read more…

By Tiffany Trader

GlobalFoundries Puts Wind in AMD’s Sails with 12nm FinFET

September 24, 2017

From its annual tech conference last week (Sept. 20), where GlobalFoundries welcomed more than 600 semiconductor professionals (reaching the Santa Clara venue Read more…

By Tiffany Trader

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last w Read more…

By John Russell

Leading Solution Providers

Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration

September 12, 2017

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The Read more…

By John Russell

Perspective: What Really Happened at SC17?

November 22, 2017

SC is over. Now comes the myriad of follow-ups. Inboxes are filled with templated emails from vendors and other exhibitors hoping to win a place in the post-SC thinking of booth visitors. Attendees of tutorials, workshops and other technical sessions will be inundated with requests for feedback. Read more…

By Andrew Jones

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Tensors Come of Age: Why the AI Revolution Will Help HPC

November 13, 2017

Thirty years ago, parallel computing was coming of age. A bitter battle began between stalwart vector computing supporters and advocates of various approaches to parallel computing. IBM skeptic Alan Karp, reacting to announcements of nCUBE’s 1024-microprocessor system and Thinking Machines’ 65,536-element array, made a public $100 wager that no one could get a parallel speedup of over 200 on real HPC workloads. Read more…

By John Gustafson & Lenore Mullin

Flipping the Flops and Reading the Top500 Tea Leaves

November 13, 2017

The 50th edition of the Top500 list, the biannual publication of the world’s fastest supercomputers based on public Linpack benchmarking results, was released Read more…

By Tiffany Trader

Intel Launches Software Tools to Ease FPGA Programming

September 5, 2017

Field Programmable Gate Arrays (FPGAs) have a reputation for being difficult to program, requiring expertise in specialty languages, like Verilog or VHDL. Easin Read more…

By Tiffany Trader

HPC Chips – A Veritable Smorgasbord?

October 10, 2017

For the first time since AMD's ill-fated launch of Bulldozer the answer to the question, 'Which CPU will be in my next HPC system?' doesn't have to be 'Whichever variety of Intel Xeon E5 they are selling when we procure'. Read more…

By Dairsie Latimer

Share This