Memory Allocation in Operating System
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This report discusses different memory allocation algorithms used in single and multicore processors for efficient memory allocation and process execution. The algorithms reviewed include Heap Data Management Algorithm, MN-MATE algorithm architecture, Memory Management Thread, Load-Balancing Stream Processing Middleware algorithm, Cache Optimization Algorithm Techniques, and CMCP Page Replacement Algorithm.
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Running head: MEMORY ALLOCATION IN OPERATING SYSTEM
Memory allocation in Operating system
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Memory allocation in Operating system
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1MEMORY ALLOCATION IN OPERATING SYSTEM
Table of Contents
Introduction................................................................................................................................2
Algorithms used for the memory allocation...............................................................................2
Heap Data Management Algorithm for LLM Multi-core Processors....................3
MN-MATE algorithm architecture for Multi-core Processors..............................4
Memory Management Thread for Heap Allocation Intensive Sequential
Applications.......................................................................................................................4
Load-Balancing Stream Processing Middleware algorithm..................................5
Cache Optimization Algorithm Techniques...........................................................6
CMCP Page Replacement Algorithm....................................................................6
Conclusion..................................................................................................................................7
References..................................................................................................................8
Appendix:.................................................................................................................................10
Annotated Bibliography...........................................................................................10
Table of Contents
Introduction................................................................................................................................2
Algorithms used for the memory allocation...............................................................................2
Heap Data Management Algorithm for LLM Multi-core Processors....................3
MN-MATE algorithm architecture for Multi-core Processors..............................4
Memory Management Thread for Heap Allocation Intensive Sequential
Applications.......................................................................................................................4
Load-Balancing Stream Processing Middleware algorithm..................................5
Cache Optimization Algorithm Techniques...........................................................6
CMCP Page Replacement Algorithm....................................................................6
Conclusion..................................................................................................................................7
References..................................................................................................................8
Appendix:.................................................................................................................................10
Annotated Bibliography...........................................................................................10
2MEMORY ALLOCATION IN OPERATING SYSTEM
Introduction
With the increasing demand of higher clock speed, the number of the cores in a single
die is increased in the last decade. According to, Karavadara et al. (2017) with the increased
clock speed there are some issues were addressed that lead to the degradation of the
performance of the system in the single core processor systems. One of this issues were
memory management in this scenario, some of the algorithms that are used are, cache
partitioning algorithm.
The following report contributes to the discussion about the different memory
management algorithms that are used in the single and multicore processors in order to
efficiently manage the allocation of memory and execution of processes.
Algorithms used for the memory allocation
A multi core system within a computer has a multiple central Processing Unit or CPU
that are unified into a single core. These are also entirely independent of each other and the
course perform the computing tasks that it luminary in nature for running a program or
managing data or executive instruction (Imtiaz, Hameed and Min-Allah 2010). in the recent
years information communication technology or ICT has evolved in an extremity and does
the computer chip manufacturers has been targeting the higher clock speeds constantly and
trying to implement multi core processor having two cores, mainly the dual core CPU and the
eight core with IBM power 7 series (Qureshi and Patt 2006). Multi core processors have been
ideal for its utility in service because they have the ability to boost the number of users who
are able to share the server resources in a simultaneous way. On the other hand the way by
which memory management is made in a multi core processor is handled by numerous
algorithms in use. Following has been a literature review based upon the different algorithms
Introduction
With the increasing demand of higher clock speed, the number of the cores in a single
die is increased in the last decade. According to, Karavadara et al. (2017) with the increased
clock speed there are some issues were addressed that lead to the degradation of the
performance of the system in the single core processor systems. One of this issues were
memory management in this scenario, some of the algorithms that are used are, cache
partitioning algorithm.
The following report contributes to the discussion about the different memory
management algorithms that are used in the single and multicore processors in order to
efficiently manage the allocation of memory and execution of processes.
Algorithms used for the memory allocation
A multi core system within a computer has a multiple central Processing Unit or CPU
that are unified into a single core. These are also entirely independent of each other and the
course perform the computing tasks that it luminary in nature for running a program or
managing data or executive instruction (Imtiaz, Hameed and Min-Allah 2010). in the recent
years information communication technology or ICT has evolved in an extremity and does
the computer chip manufacturers has been targeting the higher clock speeds constantly and
trying to implement multi core processor having two cores, mainly the dual core CPU and the
eight core with IBM power 7 series (Qureshi and Patt 2006). Multi core processors have been
ideal for its utility in service because they have the ability to boost the number of users who
are able to share the server resources in a simultaneous way. On the other hand the way by
which memory management is made in a multi core processor is handled by numerous
algorithms in use. Following has been a literature review based upon the different algorithms
3MEMORY ALLOCATION IN OPERATING SYSTEM
used for the memory allocation system in multi core operating systems all extracted from
peer reviewed journals. These journals have been selected due to the fact that they were all
the information about the data and algorithm utilised for helping the management of memory
allocation in a feasible way for the multi core processors.
Heap Data Management Algorithm for LLM Multi-core Processors
The first people and review presents scheme that has the ability to manage heap data
within a local memory that has its presence within each code of unlimited local memory or
LLM multi core processor. The journal article clearly presents how it feasibly manages heap
data using software cache in a process which is semi automatic in nature (Karavadara et al.
2017). The management of the heap data offer code also requires changing of the software
cache through changes made in the codes of different threads. The journal article focuses on
the cross state modifications that occur in the algorithm which are difficult to code as well as
equally difficult to debug. This only can become much more difficult when the number of
cores of the processes increases. The paper proposes a semi-automatic as well as a scalable
scheme for the management of heap data which has the ability to hide the complexity in a
library utilising a programming interface which is natural. In addition to that the embedded
application in which the maximum heap size is achievable at the time of compilation the
people processes a proposal for the Optimisation on the heap management with significantly
improve the performance of the application (Khatoon & Mirza 2015). The experiments for
the checking of the algorithm has been made on several Benchmarks regarding the MiBench
which executes for the on the Sony PlayStation 3. This make sure of the implementation
regarding the heap data management algorithm for multiple processes which makes sure that
the scheme proposed in the paper is easy for use and if the size of heap data at a maximum
level can be known then the Optimisation process of the entire application can be improved
on a performance level by the average of 14 per cent.
used for the memory allocation system in multi core operating systems all extracted from
peer reviewed journals. These journals have been selected due to the fact that they were all
the information about the data and algorithm utilised for helping the management of memory
allocation in a feasible way for the multi core processors.
Heap Data Management Algorithm for LLM Multi-core Processors
The first people and review presents scheme that has the ability to manage heap data
within a local memory that has its presence within each code of unlimited local memory or
LLM multi core processor. The journal article clearly presents how it feasibly manages heap
data using software cache in a process which is semi automatic in nature (Karavadara et al.
2017). The management of the heap data offer code also requires changing of the software
cache through changes made in the codes of different threads. The journal article focuses on
the cross state modifications that occur in the algorithm which are difficult to code as well as
equally difficult to debug. This only can become much more difficult when the number of
cores of the processes increases. The paper proposes a semi-automatic as well as a scalable
scheme for the management of heap data which has the ability to hide the complexity in a
library utilising a programming interface which is natural. In addition to that the embedded
application in which the maximum heap size is achievable at the time of compilation the
people processes a proposal for the Optimisation on the heap management with significantly
improve the performance of the application (Khatoon & Mirza 2015). The experiments for
the checking of the algorithm has been made on several Benchmarks regarding the MiBench
which executes for the on the Sony PlayStation 3. This make sure of the implementation
regarding the heap data management algorithm for multiple processes which makes sure that
the scheme proposed in the paper is easy for use and if the size of heap data at a maximum
level can be known then the Optimisation process of the entire application can be improved
on a performance level by the average of 14 per cent.
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4MEMORY ALLOCATION IN OPERATING SYSTEM
MN-MATE algorithm architecture for Multi-core Processors
In another paper the author Qureshi and Patt (2016), suggests that the Technologies
which have been emerging has now using an on chip memory which is non-volatile in nature
known as the NVRAM. This is lead into a shift in paradigm for the computer architecture.
With the utility of this new on chip memory the non-volatile memory is previously in news
like the PRAM and the viable DRAM could have been replaced with acquiring competitive
speed at a much lower consumption of power (Qureshi and Patt 2006). This mitigation of
overuse of extra energy and memory we'll have given rise to proposal of a new architecture
within the hierarchical and hybrid main memory for a multi core system known as MN-
MATE. This is known as M1 Memory which is the replacement of the conventional DRAM
memory. The entire design and the evaluation of the management of the techniques in an
effective way has been achieved and the algorithm has given rise to a high performance and
comparatively lower energy has been used. Even in the hierarchical memory management the
hybrid memory management and file caching has been created efficiently with the utility of
this algorithm. Further in the paper it has been revealed with the matching as a service
application that the algorithm proposed in this paper has the ability to improve the
performance and reduce usage of energy.
Memory Management Thread for Heap Allocation Intensive Sequential Applications
As per the review of another peered reviewed journal article it can be sent that
dynamic memory management has been one of the most ubiquitous and expensive operations
for the utility of C and C++ applications. This paper understands that multiprocessor acts like
a mainstream architecture which is much more important for investigation regarding in
memory management and exploitation of the multi core parallelism. the people proposes
away by which the exploiting of the multi core parallelism in the dynamic memory
management of sequential applications can work for deallocating functions which can be
MN-MATE algorithm architecture for Multi-core Processors
In another paper the author Qureshi and Patt (2016), suggests that the Technologies
which have been emerging has now using an on chip memory which is non-volatile in nature
known as the NVRAM. This is lead into a shift in paradigm for the computer architecture.
With the utility of this new on chip memory the non-volatile memory is previously in news
like the PRAM and the viable DRAM could have been replaced with acquiring competitive
speed at a much lower consumption of power (Qureshi and Patt 2006). This mitigation of
overuse of extra energy and memory we'll have given rise to proposal of a new architecture
within the hierarchical and hybrid main memory for a multi core system known as MN-
MATE. This is known as M1 Memory which is the replacement of the conventional DRAM
memory. The entire design and the evaluation of the management of the techniques in an
effective way has been achieved and the algorithm has given rise to a high performance and
comparatively lower energy has been used. Even in the hierarchical memory management the
hybrid memory management and file caching has been created efficiently with the utility of
this algorithm. Further in the paper it has been revealed with the matching as a service
application that the algorithm proposed in this paper has the ability to improve the
performance and reduce usage of energy.
Memory Management Thread for Heap Allocation Intensive Sequential Applications
As per the review of another peered reviewed journal article it can be sent that
dynamic memory management has been one of the most ubiquitous and expensive operations
for the utility of C and C++ applications. This paper understands that multiprocessor acts like
a mainstream architecture which is much more important for investigation regarding in
memory management and exploitation of the multi core parallelism. the people proposes
away by which the exploiting of the multi core parallelism in the dynamic memory
management of sequential applications can work for deallocating functions which can be
5MEMORY ALLOCATION IN OPERATING SYSTEM
done by spinning of memory allocation. This paper focuses on the aim of the study which
would put forward an efficient design and implementation of the memory management thread
or MMT such that there would be no need if the memory management library underline that
will require the library to be offloaded (Majo and Gross 2011). The paper proposes the idea
that using the allocation intensive Benchmarks in heap memory management MMT approach
can achieve average speed up ratio.
According to the contrary presented by another article the multi core processor has
been represented as going through an evolutionary change while setting up a new goal for the
high performance computing or HPC. However this algorithm proposed by the authors in the
journal article put forward that parallelism is a feature of multi core processors which is pre-
existing. therefore the people presents a description of the progression of the industry and
evolution of some of the challenges that are being faced by the multi core processors and who
proposed solutions that have been identified as a counter attack to the challenges faced by
multi core processors.
Load-Balancing Stream Processing Middleware algorithm
With the challenges with multi core processor has there also is a new technology of
tiled multi-core architecture that has become extremely popular in the latest era. The memory
management approach goes to critical challenges during the programming of several tiled
multi-core architecture available at the use of efficient resources. The hierarchical memory
management for a load balancing stream processing middleware helps to port LPEL, which is
a dynamic load balancing middleware utilise for the upstream processing to a single chip
cloud computer or SCC. The author of the journal article proposes that tiled architectures and
this algorithm have much in similarity which works much better than an MPI-based
implementation.
done by spinning of memory allocation. This paper focuses on the aim of the study which
would put forward an efficient design and implementation of the memory management thread
or MMT such that there would be no need if the memory management library underline that
will require the library to be offloaded (Majo and Gross 2011). The paper proposes the idea
that using the allocation intensive Benchmarks in heap memory management MMT approach
can achieve average speed up ratio.
According to the contrary presented by another article the multi core processor has
been represented as going through an evolutionary change while setting up a new goal for the
high performance computing or HPC. However this algorithm proposed by the authors in the
journal article put forward that parallelism is a feature of multi core processors which is pre-
existing. therefore the people presents a description of the progression of the industry and
evolution of some of the challenges that are being faced by the multi core processors and who
proposed solutions that have been identified as a counter attack to the challenges faced by
multi core processors.
Load-Balancing Stream Processing Middleware algorithm
With the challenges with multi core processor has there also is a new technology of
tiled multi-core architecture that has become extremely popular in the latest era. The memory
management approach goes to critical challenges during the programming of several tiled
multi-core architecture available at the use of efficient resources. The hierarchical memory
management for a load balancing stream processing middleware helps to port LPEL, which is
a dynamic load balancing middleware utilise for the upstream processing to a single chip
cloud computer or SCC. The author of the journal article proposes that tiled architectures and
this algorithm have much in similarity which works much better than an MPI-based
implementation.
6MEMORY ALLOCATION IN OPERATING SYSTEM
Cache Optimization Algorithm Techniques
A multi core processor has the ability to possess processor memory bandwidth which
forms a bottleneck as a result of the implementation of numerous processor cores sharing the
same memory interface or bus or processor (Blagodurov et al. 2010). The on chip memory
hierarchy in multi core processor has thus made itself an important resource which should
have efficient management so that the above problem does not occur. With conducting a
survey on all the proposed techniques in the recent publications it can be presented that the
effectiveness of the techniques utilised in the recent trip multiprocessors gained the most
appropriate assessment Technology. In addition to that, there is win an identification of the
cache Optimisation techniques which has been identified for the utility in single core
processors however it has not been implemented in multi-core processors. Due to this the
effectiveness of cache optimisation cannot be examine further within multi core processors.
CMCP Page Replacement Algorithm
Along with all the journal articles reviewed and algorithms utilised for memory
management in multi core processors have been identified there is also a journal article
devised on the idea of CMCP, which forms a page replacement policy for the system level
hierarchical memory management working on multi core processors (Gerofi et al. 2013). The
state of the art page replacement policies like the LIC policy do not understand the
requirement of masses multicore processing since they always have been a leukocyte of
buffer in validations. The buffers fail to collect the statistics for page usage. However the
implementation of the experimental 64kB page has been able to support the Xeon phi, which
is able to reveal and evaluate the proposal algorithm on various applications (Gerofi et al.
2014).
Cache Optimization Algorithm Techniques
A multi core processor has the ability to possess processor memory bandwidth which
forms a bottleneck as a result of the implementation of numerous processor cores sharing the
same memory interface or bus or processor (Blagodurov et al. 2010). The on chip memory
hierarchy in multi core processor has thus made itself an important resource which should
have efficient management so that the above problem does not occur. With conducting a
survey on all the proposed techniques in the recent publications it can be presented that the
effectiveness of the techniques utilised in the recent trip multiprocessors gained the most
appropriate assessment Technology. In addition to that, there is win an identification of the
cache Optimisation techniques which has been identified for the utility in single core
processors however it has not been implemented in multi-core processors. Due to this the
effectiveness of cache optimisation cannot be examine further within multi core processors.
CMCP Page Replacement Algorithm
Along with all the journal articles reviewed and algorithms utilised for memory
management in multi core processors have been identified there is also a journal article
devised on the idea of CMCP, which forms a page replacement policy for the system level
hierarchical memory management working on multi core processors (Gerofi et al. 2013). The
state of the art page replacement policies like the LIC policy do not understand the
requirement of masses multicore processing since they always have been a leukocyte of
buffer in validations. The buffers fail to collect the statistics for page usage. However the
implementation of the experimental 64kB page has been able to support the Xeon phi, which
is able to reveal and evaluate the proposal algorithm on various applications (Gerofi et al.
2014).
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7MEMORY ALLOCATION IN OPERATING SYSTEM
Conclusion
Thus, it can be concluded from the above review of journals on algorithms based on
memory management in multi core processors that all the algorithms used in different
methods have clearly one goal of managing the extensive amount of data generated due to the
numerous calls present within the processors. The journal article follows the structure of an
ideal peer reviewed journal but Falls short in describing the main features of how they can be
utilised with the help of different development methods physically within the organisation.
Conclusion
Thus, it can be concluded from the above review of journals on algorithms based on
memory management in multi core processors that all the algorithms used in different
methods have clearly one goal of managing the extensive amount of data generated due to the
numerous calls present within the processors. The journal article follows the structure of an
ideal peer reviewed journal but Falls short in describing the main features of how they can be
utilised with the help of different development methods physically within the organisation.
8MEMORY ALLOCATION IN OPERATING SYSTEM
References
Blagodurov, S., Zhuravlev, S., Fedorova, A. and Kamali, A., 2010, September. A case for
NUMA-aware contention management on multicore systems. In Proceedings of the 19th
international conference on Parallel architectures and compilation techniques (pp. 557-558).
ACM.
Gerofi, B., Shimada, A., Hori, A. and Ishikawa, Y., 2013, May. Partially separated page
tables for efficient operating system assisted hierarchical memory management on
heterogeneous architectures. In Cluster, Cloud and Grid Computing (CCGrid), 2013 13th
IEEE/ACM International Symposium on (pp. 360-368). IEEE.
Gerofi, B., Shimada, A., Hori, A., Masamichi, T. and Ishikawa, Y., 2014, June. CMCP: a
novel page replacement policy for system level hierarchical memory management on many-
cores. In Proceedings of the 23rd international symposium on High-performance parallel and
distributed computing (pp. 73-84). ACM.
Imtiaz, S.Y., Hameed, A. and Min-Allah, N., 2010, Multi-core Technology: An overview.
In We are pleased to present the Workshop Proceedings of the 32nd Annual Con-ference on
Artificial Intelligence (KI 2009), which is held on September 15-18 in Paderborn. This year
the volume includes papers or abstracts of ten workshops: 3rd Workshop on Behavior
Monitoring and Interpretation-Well Being, Complex (p. 126).
Karavadara, N., Zolda, M., Nguyen, V.T.N. and Kirner, R., 2017, A Hierarchical Memory
Management for a Load-Balancing Stream Processing Middleware on Tiled Architectures⋆.
Khatoon, H., & Mirza, S. H., 2015, Cache Optimization Techniques for Multi core
Processors.
References
Blagodurov, S., Zhuravlev, S., Fedorova, A. and Kamali, A., 2010, September. A case for
NUMA-aware contention management on multicore systems. In Proceedings of the 19th
international conference on Parallel architectures and compilation techniques (pp. 557-558).
ACM.
Gerofi, B., Shimada, A., Hori, A. and Ishikawa, Y., 2013, May. Partially separated page
tables for efficient operating system assisted hierarchical memory management on
heterogeneous architectures. In Cluster, Cloud and Grid Computing (CCGrid), 2013 13th
IEEE/ACM International Symposium on (pp. 360-368). IEEE.
Gerofi, B., Shimada, A., Hori, A., Masamichi, T. and Ishikawa, Y., 2014, June. CMCP: a
novel page replacement policy for system level hierarchical memory management on many-
cores. In Proceedings of the 23rd international symposium on High-performance parallel and
distributed computing (pp. 73-84). ACM.
Imtiaz, S.Y., Hameed, A. and Min-Allah, N., 2010, Multi-core Technology: An overview.
In We are pleased to present the Workshop Proceedings of the 32nd Annual Con-ference on
Artificial Intelligence (KI 2009), which is held on September 15-18 in Paderborn. This year
the volume includes papers or abstracts of ten workshops: 3rd Workshop on Behavior
Monitoring and Interpretation-Well Being, Complex (p. 126).
Karavadara, N., Zolda, M., Nguyen, V.T.N. and Kirner, R., 2017, A Hierarchical Memory
Management for a Load-Balancing Stream Processing Middleware on Tiled Architectures⋆.
Khatoon, H., & Mirza, S. H., 2015, Cache Optimization Techniques for Multi core
Processors.
9MEMORY ALLOCATION IN OPERATING SYSTEM
Liu, L., Cui, Z., Xing, M., Bao, Y., Chen, M. and Wu, C., 2012, September. A software
memory partition approach for eliminating bank-level interference in multicore systems.
In Proceedings of the 21st international conference on Parallel architectures and
compilation techniques (pp. 367-376). ACM.
Majo, Z. and Gross, T.R., 2011, June. Memory management in NUMA multicore systems:
trapped between cache contention and interconnect overhead. In AcmSigplan Notices (Vol.
46, No. 11, pp. 11-20). ACM.
Qureshi, M.K. and Patt, Y.N., 2006, December. Utility-based cache partitioning: A low-
overhead, high-performance, runtime mechanism to partition shared caches.
In Microarchitecture, 2006. MICRO-39. 39th Annual IEEE/ACM International Symposium
on (pp. 423-432). IEEE.
Zlateski, A., Lee, K. and Seung, H.S., 2016, May. ZNN--A Fast and Scalable Algorithm for
Training 3D Convolutional Networks on Multi-core and Many-Core Shared Memory
Machines. In Parallel and Distributed Processing Symposium, 2016 IEEE International (pp.
801-811). IEEE.
Liu, L., Cui, Z., Xing, M., Bao, Y., Chen, M. and Wu, C., 2012, September. A software
memory partition approach for eliminating bank-level interference in multicore systems.
In Proceedings of the 21st international conference on Parallel architectures and
compilation techniques (pp. 367-376). ACM.
Majo, Z. and Gross, T.R., 2011, June. Memory management in NUMA multicore systems:
trapped between cache contention and interconnect overhead. In AcmSigplan Notices (Vol.
46, No. 11, pp. 11-20). ACM.
Qureshi, M.K. and Patt, Y.N., 2006, December. Utility-based cache partitioning: A low-
overhead, high-performance, runtime mechanism to partition shared caches.
In Microarchitecture, 2006. MICRO-39. 39th Annual IEEE/ACM International Symposium
on (pp. 423-432). IEEE.
Zlateski, A., Lee, K. and Seung, H.S., 2016, May. ZNN--A Fast and Scalable Algorithm for
Training 3D Convolutional Networks on Multi-core and Many-Core Shared Memory
Machines. In Parallel and Distributed Processing Symposium, 2016 IEEE International (pp.
801-811). IEEE.
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10MEMORY ALLOCATION IN OPERATING SYSTEM
Appendix:
Annotated Bibliography
Zlateski, A., Lee, K. and Seung, H.S., 2016, May. ZNN--A Fast and Scalable Algorithm
for Training 3D Convolutional Networks on Multi-core and Many-Core Shared
Memory Machines. In Parallel and Distributed Processing Symposium, 2016 IEEE
International (pp. 801-811). IEEE.
This paper has been selected for the primary reason of it being convenient to the
subject as well as being a peer reviewed journal that has been well solicited for. The paper
suggests a proper vision on a developed algorithm that states a well expanded fact of the 3D
Convolutional Networks on both multi core as well as many core Shared Memory Machines.
This has been a new approach towards the latest advancements of the Convolutional
Networks, which has become a popular approach towards the computational vision of
CovNet Trainings.
Liu, L., Cui, Z., Xing, M., Bao, Y., Chen, M. and Wu, C., 2012, September. A software
memory partition approach for eliminating bank-level interference in multicore
systems. In Proceedings of the 21st international conference on Parallel architectures and
compilation techniques (pp. 367-376). ACM.
This paper has been selected in order to make sure that the literatures reviewed for the
purpose goes through different algorithms used for the purpose. This peer reviewed article
focuses on the memory partition approach for the purpose of eliminating the bank level
interference in multi core processors. The paper presents a clear idea on how the bank level
interference creates a lag in the systems and performance degradation of multi core
processors and that is why this is a convenient source of creating a review of the articles.
Appendix:
Annotated Bibliography
Zlateski, A., Lee, K. and Seung, H.S., 2016, May. ZNN--A Fast and Scalable Algorithm
for Training 3D Convolutional Networks on Multi-core and Many-Core Shared
Memory Machines. In Parallel and Distributed Processing Symposium, 2016 IEEE
International (pp. 801-811). IEEE.
This paper has been selected for the primary reason of it being convenient to the
subject as well as being a peer reviewed journal that has been well solicited for. The paper
suggests a proper vision on a developed algorithm that states a well expanded fact of the 3D
Convolutional Networks on both multi core as well as many core Shared Memory Machines.
This has been a new approach towards the latest advancements of the Convolutional
Networks, which has become a popular approach towards the computational vision of
CovNet Trainings.
Liu, L., Cui, Z., Xing, M., Bao, Y., Chen, M. and Wu, C., 2012, September. A software
memory partition approach for eliminating bank-level interference in multicore
systems. In Proceedings of the 21st international conference on Parallel architectures and
compilation techniques (pp. 367-376). ACM.
This paper has been selected in order to make sure that the literatures reviewed for the
purpose goes through different algorithms used for the purpose. This peer reviewed article
focuses on the memory partition approach for the purpose of eliminating the bank level
interference in multi core processors. The paper presents a clear idea on how the bank level
interference creates a lag in the systems and performance degradation of multi core
processors and that is why this is a convenient source of creating a review of the articles.
11MEMORY ALLOCATION IN OPERATING SYSTEM
Gerofi, B., Shimada, A., Hori, A., Masamichi, T. and Ishikawa, Y., 2014, June. CMCP:
a novel page replacement policy for system level hierarchical memory management on
many-cores. In Proceedings of the 23rd international symposium on High-performance
parallel and distributed computing (pp. 73-84). ACM.
This article has been chosen for the reason that it effectively discusses the developed
algorithm of CMCP, a page replacement policy that works through the system level
hierarchical memory management through the multi level processors. This is a peer reviewed
article and it presents a clear idea about the algorithm and how this creates a prevalence in
co-processors if Intel, such as Xeon Phi. The paper clearly states how state of the art page
replacement policies, such as approximations of the least recently used (LRU) policy, are not
good candidates for massive many-cores.
Majo, Z. and Gross, T.R., 2011, June. Memory management in NUMA multicore
systems: trapped between cache contention and interconnect overhead. In AcmSigplan
Notices (Vol. 46, No. 11, pp. 11-20). ACM.
This paper is selected for presenting the approach of memory management in multi
core processor with a new developed algorithm in the NUMA multi core systems that
remains trapped in between cache contentions and incorrect overheads.
Qureshi, M.K. and Patt, Y.N., 2006, December. Utility-based cache partitioning: A low-
overhead, high-performance, runtime mechanism to partition shared caches.
In Microarchitecture, 2006. MICRO-39. 39th Annual IEEE/ACM International
Symposium on (pp. 423-432). IEEE.
This paper has been selected for being a well informed peer reviewed source of the
utility based cache partitioning. This algorithm serves the purpose of being a low over head
Gerofi, B., Shimada, A., Hori, A., Masamichi, T. and Ishikawa, Y., 2014, June. CMCP:
a novel page replacement policy for system level hierarchical memory management on
many-cores. In Proceedings of the 23rd international symposium on High-performance
parallel and distributed computing (pp. 73-84). ACM.
This article has been chosen for the reason that it effectively discusses the developed
algorithm of CMCP, a page replacement policy that works through the system level
hierarchical memory management through the multi level processors. This is a peer reviewed
article and it presents a clear idea about the algorithm and how this creates a prevalence in
co-processors if Intel, such as Xeon Phi. The paper clearly states how state of the art page
replacement policies, such as approximations of the least recently used (LRU) policy, are not
good candidates for massive many-cores.
Majo, Z. and Gross, T.R., 2011, June. Memory management in NUMA multicore
systems: trapped between cache contention and interconnect overhead. In AcmSigplan
Notices (Vol. 46, No. 11, pp. 11-20). ACM.
This paper is selected for presenting the approach of memory management in multi
core processor with a new developed algorithm in the NUMA multi core systems that
remains trapped in between cache contentions and incorrect overheads.
Qureshi, M.K. and Patt, Y.N., 2006, December. Utility-based cache partitioning: A low-
overhead, high-performance, runtime mechanism to partition shared caches.
In Microarchitecture, 2006. MICRO-39. 39th Annual IEEE/ACM International
Symposium on (pp. 423-432). IEEE.
This paper has been selected for being a well informed peer reviewed source of the
utility based cache partitioning. This algorithm serves the purpose of being a low over head
12MEMORY ALLOCATION IN OPERATING SYSTEM
algorithm delivering high performance, which increases the runtime mechanism to partition
shared caches.
algorithm delivering high performance, which increases the runtime mechanism to partition
shared caches.
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