This document summarizes the performance of the 9 Punjab battalion during the 1965 war with India. The battalion was part of the 12th Division of the Pakistan Army and was tasked with capturing the town of Chhamb. Despite having significant superiority in tanks and artillery, the 12th Division failed to cross the Tawi River on the first day. The 9th Punjab battalion suffered 15 killed and 31 wounded but managed to form a bridgehead across the Tawi. After the war, the battalion was praised for its performance and received several awards, though its strategic impact was limited due to the overall failure of Operation Grand Slam.
Battle of Gangiri-Heavy Price paid by HM 6 Dragoon Guards for Gallantry Agha A
Battle of Gangiri-Heavy Price paid by HM 6 Dragoon Guards for Gallantry https://www.academia.edu/52632772/Battle_of_Gangiri_Heavy_Price_paid_by_HM_6_Dragoon_Guards_for_Gallantry via @academia
WHY PAKISTAN ARMY OR INDIAN ARMY CAN NEVER PRODUCE A MUSTAFA KAMAL- SOMETHING...Agha A
WHY PAKISTAN ARMY OR INDIAN ARMY CAN NEVER PRODUCE A MUSTAFA KAMAL- SOMETHING SERIOUSLY WRONG IN THE GENES
April 2020
DOI: 10.13140/RG.2.2.20723.27689
Project: MILITARY HISTORY
Agha H Amin
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Battle of Gangiri-Heavy Price paid by HM 6 Dragoon Guards for Gallantry Agha A
Battle of Gangiri-Heavy Price paid by HM 6 Dragoon Guards for Gallantry https://www.academia.edu/52632772/Battle_of_Gangiri_Heavy_Price_paid_by_HM_6_Dragoon_Guards_for_Gallantry via @academia
WHY PAKISTAN ARMY OR INDIAN ARMY CAN NEVER PRODUCE A MUSTAFA KAMAL- SOMETHING...Agha A
WHY PAKISTAN ARMY OR INDIAN ARMY CAN NEVER PRODUCE A MUSTAFA KAMAL- SOMETHING SERIOUSLY WRONG IN THE GENES
April 2020
DOI: 10.13140/RG.2.2.20723.27689
Project: MILITARY HISTORY
Agha H Amin
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
【社内勉強会資料_Octo: An Open-Source Generalist Robot Policy】
9 punjab in 1965 war
1.
2. This battalion was a part of 12 Division (102 Brigade) . It
was regarded as one of the finest battalions of the
Pakistan Army and was assigned the division’s principal
task of capturing Chhamb.1
As the map above indicates Pakistan’s 12 Division in this
sector enjoyed very significant overall superiority over
the weak Indian screen type positions , by virtue of
massive superiority in tanks and artillery.
1
Page-204- VETERAN CAMPAIGNERS-A HISTORY OF THE
PUNJAB REGIMENT-1759-1981-Op cit.
5. While 9 Punjab performed outstandingly on the first and
second day of Operation Grand Slam , Pakistan’s 12
6. Division’s performance on the first day of the war was
operationally pathetic in failing to cross Tawi despite
massive superiority in tanks and artillery and encircling
and destroying the very weak Indian 191 Brigade.
A bridgehead across Tawi was formed by 10 Brigade ,
against no Indian opposition as map below indicates:--
9 Punjab’s operations across Tawi river commencing
from 4th
September 1965 till ceasefire are indicated by
two maps below and are exhaustively self explanatory.
7.
8.
9. The battalion suffered 15 killed 31 wounded and 3
missing casualties in whole of 1965 war .2
These
casualties are not very high for an infantry battalion
keeping in view its total strength which is over 800 . My
own regiment 11 Cavalry (FF) (tank regiment strength
is about half of infantry battalion) which fought
alongside 9 Punjab in 1965 war suffered 19 killed in a
single day of fighting.
The battalion’s low casualties may be ascribed to the
fact that Pakistan Army enjoyed considerably
overwhelming superiority in tanks and artillery in this
sector.
The battalion won the following awards :--3
Sitara I Jurrat -TWO
Tamgha I Jurrat -FOUR
IMTIAZI SANAD -THREE
The Sitara e Jurrats were won by the commanding
officer lieutenant colonel Hanif and Major Musarrat
Nawaz.4
2
Page-509- VETERAN CAMPAIGNERS-A HISTORY OF THE
PUNJAB REGIMENT-1759-1981-
3
Page-206- VETERAN CAMPAIGNERS-A HISTORY OF THE
PUNJAB REGIMENT-1759-1981-
4
Page-516- VETERAN CAMPAIGNERS-A HISTORY OF THE
PUNJAB REGIMENT-1759-1981-
10. The battalion lost no officer in the war.
The battalion performed outstandingly in the war and
was universally praised in the Pakistan Army both in
published accounts and by general word of mouth.
The battalions outstanding performance apart ,
Operation Grand Slam was a strategic and operational
failure , hence the battalion’s net strategic impact on
war was NIL.
9 Punjab was one of finest battalions of Pakistan Army
as fondly remembered by my regiment who fought
alongside this great battalion in Operation Grand Slam.