title: Keynote: Going to university—Blended strategies for learning and teaching in a modern tertiary context

authors: Forbes, Dianne Leslie

abstract: This think piece is a follow-up to a keynote delivered at the biennial DEANZ Conference, at the University of Waikato in Hamilton, New Zealand, in April 2016. It explores the University of Waikato’s Mixed Media Pathway. Dianne Forbes ponders her own experiences as a tertiary student, considers some of the changes and challenges facing universities today, and presents one response to these changes in the form of blended learning. The Bachelor of Teaching, Mixed Media Presentation—an initial teacher education degree at the University of Waikato—is used to illustrate the benefits and challenges of blended learning for students and lecturers. It is proposed that students based on campus can benefit from blended learning, just as geographically dispersed students can. Going to university can comprise active learning partnerships at a range of physical locations.

text: Keynote: Going to university—Blended strategies for learning and teaching in a modern tertiary context This think piece is a follow-up to a keynote delivered at the biennial DEANZ Conference, at the University of Waikato in Hamilton, New Zealand, in April 2016. It explores the University of Waikato’s Mixed Media Pathway. Dianne Forbes ponders her own experiences as a tertiary student, considers some of the changes and challenges facing universities today, and presents one response to these changes in the form of blended learning. The Bachelor of Teaching, Mixed Media Presentation—an initial teacher education degree at the University of Waikato—is used to illustrate the benefits and challenges of blended learning for students and lecturers. It is proposed that students based on campus can benefit from blended learning, just as geographically dispersed students can. Going to university can comprise active learning partnerships at a range of physical locations.

year: 2016

title: Bandwidth-optimal random shuffling for GPUs

authors: Mitchell, Rory

subjects: computer science

abstract: Linear-time algorithms that are traditionally used to shuffle data on CPUs, such as the method of Fisher-Yates, are not well suited to implementation on GPUs due to inherent sequential dependencies, and existing parallel shuffling algorithms are unsuitable for GPU architectures because they incur a large number of read/write operations to high latency global memory. To address this, we provide a method of generating pseudo-random permutations in parallel by fusing suitable pseudo-random bijective functions with stream compaction operations. Our algorithm, termed “bijective shuffle” trades increased per-thread arithmetic operations for reduced global memory transactions. It is work-efficient, deterministic, and only requires a single global memory read and write per shuffle input, thus maximising use of global memory bandwidth. To empirically demonstrate the correctness of the algorithm, we develop a statistical test for the quality of pseudo-random permutations based on kernel space embeddings. Experimental results show that the bijective shuffle algorithm outperforms competing algorithms on GPUs, showing improvements of between one and two orders of magnitude and approaching peak device bandwidth.

text: Bandwidth-optimal random shuffling for GPUs Linear-time algorithms that are traditionally used to shuffle data on CPUs, such as the method of Fisher-Yates, are not well suited to implementation on GPUs due to inherent sequential dependencies, and existing parallel shuffling algorithms are unsuitable for GPU architectures because they incur a large number of read/write operations to high latency global memory. To address this, we provide a method of generating pseudo-random permutations in parallel by fusing suitable pseudo-random bijective functions with stream compaction operations. Our algorithm, termed “bijective shuffle” trades increased per-thread arithmetic operations for reduced global memory transactions. It is work-efficient, deterministic, and only requires a single global memory read and write per shuffle input, thus maximising use of global memory bandwidth. To empirically demonstrate the correctness of the algorithm, we develop a statistical test for the quality of pseudo-random permutations based on kernel space embeddings. Experimental results show that the bijective shuffle algorithm outperforms competing algorithms on GPUs, showing improvements of between one and two orders of magnitude and approaching peak device bandwidth.

year: 2022

title: Ue Waerea

authors: Tuaupiki, Jackie Whetumarama

subjects: Waerea

abstract: Mai i Mōkau ki Tāmaki, Mangatoatoa, Pare-Waikato, Pare-Hauraki, Te Kaokaoroa o Pātetere, ko te whakapono, nā Tāwhaki i piki te poutama ki te tāhuhu matapu, ka riro mai i a ia ngā kete o te wānanga. E kīngia ai, ko te pūtake tērā o te mātauranga Māori. Hei tā Wiri (2001), nā te mātauranga Māori, ko te mātauranga Māori ā-waha. Nāna, ko te waiata. Nā te waiata, ko te karakia. Kei raro i te karakia, ko te takere kaupapa tēnei, ko te waerea. Ko te whāinga o tēnei tuhituhinga, he rangahau i ngā pūtake o te waerea me te āta titiro ki ngā kaupapa kei a ia me tōna kawe i roto i aua kaupapa i ngā wā o mua, ā, nō nāianei hoki. Ko te waerea te pane o ngā karakia Māori ki roto o Tainui, otirā, ki roto i ngētehi o ngā whakaritenga, ā, ka tirohia ngēnei whakaritenga e rere ai te waerea, pēnei i te tomo whare, i te tomo urupā, i te takahi whare, i te whakamānu waka me te maha o ngā mahi a te ao Māori ki roto o Tainui.

text: Ue Waerea Mai i Mōkau ki Tāmaki, Mangatoatoa, Pare-Waikato, Pare-Hauraki, Te Kaokaoroa o Pātetere, ko te whakapono, nā Tāwhaki i piki te poutama ki te tāhuhu matapu, ka riro mai i a ia ngā kete o te wānanga. E kīngia ai, ko te pūtake tērā o te mātauranga Māori. Hei tā Wiri (2001), nā te mātauranga Māori, ko te mātauranga Māori ā-waha. Nāna, ko te waiata. Nā te waiata, ko te karakia. Kei raro i te karakia, ko te takere kaupapa tēnei, ko te waerea. Ko te whāinga o tēnei tuhituhinga, he rangahau i ngā pūtake o te waerea me te āta titiro ki ngā kaupapa kei a ia me tōna kawe i roto i aua kaupapa i ngā wā o mua, ā, nō nāianei hoki. Ko te waerea te pane o ngā karakia Māori ki roto o Tainui, otirā, ki roto i ngētehi o ngā whakaritenga, ā, ka tirohia ngēnei whakaritenga e rere ai te waerea, pēnei i te tomo whare, i te tomo urupā, i te takahi whare, i te whakamānu waka me te maha o ngā mahi a te ao Māori ki roto o Tainui.

year: 2011-04